MX2012004620A - Integrated health data capture and analysis system. - Google Patents

Abstract

The present invention provides an integrated health care surveillance and monitoring system that provides real-time sampling, modeling, analysis, and recommended interventions. The system can be used to monitor infectious and chronic diseases. When faced with outbreak of an infectious disease agent, e.g., influenza virus, the system can identify active cases through pro-active sampling in high risk locations, such as schools or crowded commercial areas. The system can notify appropriate entities, e.g., local, regional and national governments, when an event is detected, thereby allowing for proactive management of a possible outbreak. The system also predicts the best response for deployment of scarce resources.

Description

SYSTEM. INTEGRATED CAPTURE AND ANALYSIS OF HEALTH DATA BACKGROUND OF THE INVENTION An epidemic of infectious diseases capable of spreading through a large region, for example / a continent or the whole world, can be highly costly to! the societies. Such incidences include influenza pandemic, smallpox, tuberculosis, human immune deficiency virus (HIV) and severe acute respiratory syndrome (SARS). The world bank estimated in 2008 that an influenza pandemic could cost $ 3 trillion and result in a fall of almost 5% in the global gross domestic product (GDP). The World Bank also estimated that more than 70 million people could die in the world in a severe pandemic. Others have estimated that an influenza pandemic could cause an economic recession in the United States of America, costing the country at least $ 500 billion dollars $ 675 billion in the short term. In 2003, SARS disrupted travel, commerce and the workplace in the Pacific region of Asia and cost the region approximately $ 40 billion. The SARS pandemic lasted six months, killing at least 1,000 of the 8,000 infected people in 25 countries. The city of Toronto, CA was closed to air traffic for several weeks and suffered significant financial loss.

In 2009, the spring influenza season cost billions of dollars but only lasted only a few weeks. The 2009-2010 winter influenza season is anticipated to start at the end of August and could run through April 2010. Even if work vaccines are available, their supply is expected to be limited and can not be expected to stop the flu for several months. Economic losses can be minimized if influenza can be contained by means of proactive selection that allows effective anti-viral administration and closely targeted quarantines.

The economic loss due to "evasion behaviors" is even greater than the cost of treating influenza victims. The cost includes reducing air travel, avoiding traveling to infected destinations and reducing the consumption of services, such as mass transit, meals, shopping, etc. According to the World Bank, if an influenza epidemic approaches the mortality proportions of 2.5% similar to the influenza of 1918-19, evasion behaviors would cost a region five times more than losses of mortality or absenteeism in the region. the job.

BRIEF DESCRIPTION OF THE INVENTION There is a pressing need for infrastructure to mitigate the spread of infectious diseases such as influenza when it occurs. The present invention satisfies this need by means of an integrated system that provides real-time sampling, modeling, analysis and / or recommended interventions. The system can identify active cases in an outbreak through pro-active sampling in high-risk sites, such as schools or populated commercial areas, and can allow sampling and quarantine of surrounding cases to help eradicate the outbreak. The system can also suggest an appropriate response for the deployment of scarce resources and predict the impact of such mitigation both in terms of reduction of mortality and morbidity and economic impact. In addition, the systems of the present invention can help the government provide accurate, more reliable and timely information that can reduce unnecessary evasion behavior and save billions of dollars.

In one aspect, the present invention provides a system for modeling a disease progression in a population, comprising: a static database component comprising static data concerning the disease and / or population; a dynamic database component that comprises dynamic data about the population and individual subjects; and a computer modeling component that is configured to model the data in the statistical database component and the dynamic database component, thereby modeling the disease within the population. The disease can be an infectious disease or a chronic disease.

In some embodiments, the infectious disease agent or an analyte thereof comprises an adenoviirus, Bordella pertussis, Chlamydia pneumoia, Chlamydia trachomatis, cholera toxin, cholera β-toxin, Campylobacter jejuni, cytomegalovirus, diphtheria toxin, Epstein-Barr NA , Epstein-Barr EA, Epstein-Barr VCA, Helicobacter Pylori, hepatitis B virus (HBV) core, hepatitis B virus envelope (HBV), hepatitis B virus (HBV) surface (Ay), nucleus of hepatitis C virus (HCV), hepatitis C virus (HCV) NS3, hepatitis C virus (HCV) NS4, hepatitis C virus (HCV) NS5, hepatitis A, hepatitis D, hepatitis E virus (HEV) orf2 3 D, hepatitis E virus (HEV) orf2 6 KD, hepatitis E virus (HEV) orf3 3KD, human immunodeficiency virus (HIV) -l p24, human immunodeficiency virus (HIV) -1 gp41, human immunodeficiency virus (HIV) -l gpl20, human papilloma virus (HPV), herpes simplex virus HSV-1/2, HS herpes simplex virus V-1 gD, herpes simplex virus HSV-2 gG, human T cell leukemia virus (HTLV) -l / 2, Influenza A, Influenza A H3N2, - Influenza B, Leishmania donovani, Lyme disease, mumps, M pneumoniae, M. tuberculosis, parainfluenza 1, parainfluenza 2, parainfluenza 3, poliovirus, respiratory syncytial virus (RSV), Rubella, rubella, streptolysin 0, tetanus toxin, T. pallidum 15 kd, T. pallidum p47, T cruzi, toxoplasma or Zoster varicella.

In other modalities, the disease is < an infectious disease that includes a microorganism, a microbe, a virus, a bacterium, an archaeum, a protozooario, a protista, a fungus or a microscopic plant. The virus can include influenza or HIV. The bacterium may comprise mycobacterium tuberculosis. The protozoa may include malaria.

In still other modalities, the disease is a chronic disease or condition comprising diabetes, prediabetes, insulin resistance, metabolic alteration, obesity or cardiovascular disease.

The static database component of the invention may include information about the individuals in the population. Information about individuals in the population may include one or more of age, race, sex, location, genetic factors, single nucleotide polymorphisms (SNP), family history, disease history or therapeutic history.

The static database component may also comprise information about the disease. Information about the disease may include one or more virulence, contagious capacity, mode of transmission, availability of treatment, availability of vaccine, proportion of death, recovery time, cost of treatment, infectivity, speed of recreation, speed of mutation and past buds. ¡' In some modalities, the data in the dynamic database component is updated in real time. ' In some modalities, the data in the dynamic database component comprises an indication of the disease status of individuals in the population. The indication of the disease status of an individual can be determined by measuring a biomarker, a physiological parameter or a combination thereof.

When the disease monitored by the invention is influenza, the biomarkers may include haemagglutinin and / or neuraminidase. The hemagglutinin can be selected from the group consisting of H1, H2, H3, H4, H5, H6, H7, H8, H9, H10, Hll, H12, H13, H14, H15 and H16, and the neuraminidase can be selected from the group consisting of NI, N2, N3, 4 and N5. In some embodiments, the hemagglutinin comprises Hl and the neuraminidase comprises NI. In some embodiments, the hemagglutinin comprises H5 and the neuraminidase comprises NI.

The biomarker measured by the invention can be a host antibody. For example, the biomarker can be an IgM antibody, an antibody, an IgG antibody or a IgA against a disease marker.

In some embodiments, the biomarker comprises a marker of inflammation. Such a marker of inflammation may be a cytokine or a C-reactive protein. The inflammation marker can also be IL-? ß, IL-6, IL-8, IL-10 or TNFa.

. In some embodiments, the biomarker is measured in a sample of the individual's body fluid. Exemplary body fluids include without limitation blood, plasma, serum, sputum, urine, feces, semen, mucus, lymph, saliva or nasal lavage.

In some embodiments, the physiological parameter measured by the invention comprises one or more of body weight, temperature, heart rate, blood pressure, mobility, hydration, ECG or alcohol use.

The biomarker or physiological parameter can be determined using a point-of-care device. Point-of-care devices can be deployed according to instructions determined by the computer modeling component. The point of care device can perform without limitation one or more of cartridge analysis, real-time PCR, rapid antigen tests, viral culture and immunoassay. The point of care device can measure more than one biomarker with more than 30% better accuracy and / or precision than the standard methods. In some embodiments, the system comprises a plurality of point of care devices. Point of care devices can be placed in one or more of a school, a workplace, a shopping center, a community center, a religious institution, a hospital, a health clinic, a mobile unit or a house .

The point of care device may comprise a portable intrusion. For example, the point of care device may include a portable cartridge. In some embodiments, the cartridge is configured to accept reagents to measure the biomarkers. Biomarkers can be measured according to a communicated protocol of the computer modeling component. In some embodiments, the cartridge is configured to measure a set of biomarkers of a plurality of body fluid samples.

The point of care device of the invention may include a graphical user interface configured for data entry.

In some embodiments, the point of care device is configured to communicate the biomarker or physiological parameter measurements to the computer modeling component. The communication may include wireless communication, wired communication or a combination thereof. Wireless communication includes, without limitation, WiFi, Bluetooth, Zigbee, cellular, satellite and / or WAN. The communication can also be made in a secure internet communication. In some embodiments, the point of care device is configured to perform bidirectional communications with the modeling component by computer.

In some embodiments of the system of the invention, the modeling results are updated in real time when the updated dynamic data becomes available, for example, after the computer modeling component receives updated information from a point-of-care device. .

The computer modeling component can be configured to present the modeling results to one or more of health care professionals, government agencies and individual human subjects. The computer modeling component can also be configured to predict one or more courses of action based on modeling results. The one or more courses of action are classified according to a classification parameter, including without limitation classification by financial considerations, number of affected individuals, quality of life adjusted to the year (QALY) and / or quality of life adjusted to the year (QALY ) by economic unit cost.

The one or more courses of action comprise a strategy to control the spread of the disease. The strategy to control the spread of the disease may include one or more of domestic quarantineindividual quarantine, geographical quarantine, social distancing, hospitalization, school closure, closure of the workplace, travel restrictions, closure of public transit, therapeutic treatment or intervention, prophylactic treatment or intervention, vaccination, provision of protective clothing, provision of masks and additional point-of-care tests. The strategy to control the spread of the disease may include one or more of counseling in individuals at risk or affected for behavioral modification, repeated biomarker and / or physiological measurements and reward for the individual. Still further, the strategy to control the spread of the disease may include one or more recommendations for patient triage, resource management, efficacy index for each strategy, costs of each strategy, return on investment for each strategy. The strategy to control the spread of the disease may be one or more of targeted prophylaxis, blanket prophylaxis, targeted antibiotic prophylaxis, blanket antibiotic prophylaxis, targeted anti-viral prophylaxis, blanket anti-viral prophylaxis, targeted vaccination and vaccination of blanket. Prophylaxis or targeted vaccination may be aimed; prophylaxis or vaccination for children between 1-4 years of age, children between 5-14 years of age, pregnant women, young adults between 15-30 years of age, first-line medi ^ response workers, individuals identified at high risk1 of mortality or geriatric individuals.

In some embodiments of the invention, the computer modeling component is configured to estimate a surveillance strategy based on modeling results. The surveillance strategy may include determining the disease state of an individual or group of individuals using a point-of-care device. The 'surveillance strategy can be updated when a sick individual is detected. In some modalities, the updated strategy comprises one or more tests of a house comprising the sick individual, tests of a school comprising the sick individual and evidence of a workplace comprising the sick individual. The updated strategy may also be one or more of quarantine, prophylaxis or hospitalization.

In some embodiments, the computer modeling component comprises a graphical interface to display modeling results to a user.

The computer modeling component may include a plurality of ordinary non-linear differential equations and / or a plurality of parameters. In some embodiments, the computer modeling component comprises a learning machine that updates the plurality of parameters when the static data and / or dynamic data is updated.

The data model may be configured to include a plurality of states. In some embodiments, the plurality of states comprises one or more of: susceptible individuals, prematurely exposed individuals, late-exposed individuals, prematurely infected individuals, late infected individuals, recovered individuals, individuals who died due to infection and / or associated complications, symptomatic individuals, individuals who are given therapeutic treatment, individuals who are given therapeutic and quarantine treatment, prophylactically treated individuals, vaccinated individuals, protected individuals due to vaccination, prematurely infected individuals who are hospitalized, infected individuals late that they are hospitalized, susceptible individuals who are quarantined at home, prematurely exposed individuals who are quarantined at home, late-exposed individuals who are quarantined at home, prematurely infected individuals who are placed in quarantine at home, late-infected individuals who are quarantined at home, asymptomatic individuals who are quarantined at home, susceptible individuals quarantined throughout the neighborhood, prematurely exposed individuals quarantined throughout the neighborhood, late-laid individuals in quarantine in 1, the entire neighborhood, prematurely infected individuals quarantined throughout the neighborhood, infected individuals belatedly quarantined throughout the neighborhood, asymptomatic individuals quarantined throughout the neighborhood, number of available therapeutic drug doses, antivirals and / or antibiotics available to the target population, individuals in quarantine at home who are vaccinated, quarantined individuals at home who are protected due to vaccination, individuals quarantined at home who recovered, susceptible individuals previously marked by mitigation policies for action , individuals exposed prematurely affected by policies for mitigation action, individuals exposed late affected by mitigation policies, í asymptomatic individuals affected by mitigation action policies, infected individuals prematurely affected by mitigation action policies, infected individuals, belatedly affected by mitigation policies, prophylactic-treated individuals affected by mitigation action policies, (vaccinated individuals) í affected by mitigation action policies, protected individuals affected by the action policies of. mitigation, recovered individuals affected by mitigation action policies, susceptible individuals affected by therapeutic treatment, individuals exposed prematurely affected by therapeutic treatment, individuals exposed late affected for therapeutic treatment, affected asymptomatic individuals for therapeutic treatment, infected individuals prematurely affected for therapeutic treatment, late-affected infected individuals · for therapeutic treatment, affected susceptible individuals for surveillance, individuals exposed prematurely affected for surveillance, late-affected individuals exposed for surveillance, asymptomatic individuals affected for surveillance, infected individuals prematurely affected for surveillance, late-affected infected individuals for surveillance, individuals affected prophylactics for surveillance, vaccinated individuals affected for surveillance, protected individuals affected for surveillance, susceptible individuals in quarantine in entire neighborhood affected by mitigation action policies, individuals exposed prematurely in entire quarantine neighborhood affected by mitigation action policies, individuals exposed late in quarantine in entire neighborhood affected by mitigation action policies, asymptomatic individuals in quarantine in whole neighborhood affected by mitigation action policies, individuals infected prematurely in quarantine in the entire neighborhood affected by mitigation action policies, individuals infected late in quarantine in entire neighborhood affected by mitigation action policies, treated individuals prophylactically in quarantine throughout the neighborhood affected by mitigation action policies, cumulative number of therapeutic doses administered, cumulative number of antivirals and / or antibiotics administered, cumulative number of indi viduos asymptomatic. in quarantine at home, cumulative number of symptomatic individuals quarantined at home, í cumulative number of total infected individuals, cumulative number of infected individuals who are not! in quarantine, cumulative number of infected individuals: with some action taken, cumulative number of hospitalized individuals and cumulative number of deaths.

In another aspect, the present invention provides a system for controlling the spreading of influenza in a population, comprising: a static database component comprising static data related to influenza and / or population; a dynamic database component that comprises dynamic data about * the population; and a computer modeling component1; which is configured to model the data in the static database component and the dynamic database component, thereby modeling the incidence of j; the comprising: a static database component 1 comprising static data related to HIV and / or the population; a dynamic database component that comprises dynamic data about the population; a computer modeling component that is configured to model the data in the static database component and the dynamic database component, thereby modeling the incidence of HIV within the population.

In yet another aspect, the present invention provides a system for controlling the spread of hepatitis in a population, comprising: a static database component comprising static data related to hepatitis and / or population; a dynamic database component that comprises dynamic data about the population; and a computer modeling component that is configured to model the data in the static database component and the dynamic database component, thereby modeling the incidence of hepatitis in the population.

In one aspect, the present invention provides a system for controlling the spread of diabetes in,! a population, comprising: a static database component comprising static data related to diabetes and / or population; a dynamic database component that comprises dynamic data about! the population; and a computer modeling component! which is configured to model the data in the static database component and the dynamic database component, thereby modeling the incidence of diabetes in the population. 1 INCORPORATION BY REFERENCE All publications, patents and patent applications mentioned in this specification are incorporated herein by reference to the same extent as if each publication, patent or individual patent application was specifically and individually indicated for; be incorporated by reference. ''; BRIEF DESCRIPTION OF THE FIGURES The new elements of the invention are summarized with particularity in the appended claims. A better understanding of the elements and advantages of the present invention will be obtained by reference to the following detailed description which summarizes illustrative modalities;, in which the principles of the invention are used and the attached figures of which: Figure 1 illustrates a simplified model representation. i Figure 2 illustrates a model representation taking into account several states and transitions between states.

Figure 3 illustrates an analysis for an antigen of H1N1 using sandwich complexes in four different configurations.

Figure 4A illustrates an analysis for anti-virus host antibodies. The figure illustrates a projection recovery analysis for anti-HINl host antibodies. A version is displayed using an a-Hl / -Nl configuration. Figure 4B illustrates direct analyzes for a-? 1? 1 antibodies illustrating sandwich complexes.

Figure 5 illustrates an exemplary device; which can be used in the present invention. Exemplary devices include analysis units, reagent units and other modular components.

Figure 6 illustrates two side views in section of the exemplary device that can be used in the present invention. The exemplary device comprises cavities in the housing of the device formed to accommodate an analysis unit, a reagent unit and a sampling tip.

Figure 7A demonstrates an exemplary analysis unit comprising a small tip or tubular formation. Figure 7B shows an example of a tooth tip 1 as described herein. ! i Figures 8A and 8B illustrate two examples of 'a' reagent unit comprising a cup.

Figure 9 illustrates a thin film, for example, contamination, inside the tip when a it is expelled and another liquid aspirated. I Figure 10 demonstrates an example of a system comprising a device and a fluid transfer device. j.

Figure 11 illustrates an exemplary system of the invention comprising a heating block for temperature control and a detector. ' t Figure 12 demonstrates an exemplary system in which a patient administers blood to a device and then the device is inserted into a reader. j Figure 13 illustrates the process flow1 of building a system to determine a patient's medical condition.

Figures 14A to 14E demonstrate an example of a plasma separation method in which a whole sample of sngre has been aspirated to a sample tip and a magnetic reagent is mixed and suspended with the sample, then a magnetic field is applied to the sample. the whole blood sample and magnetic reagent mixture. The plasma sample of sa gre The separated can then be distributed to a cavity of the device.

Figure 15 shows an exemplary method of a control analysis as described herein comprising a known amount of control analyte.

Figure 16 illustrates an exemplary embodiment of a health shield user interface.

Figure 17 illustrates another exemplary embodiment of a health shielding interface.

Figure 18 illustrates the simulation of the La Gloria outbreak of 2009 with and without mitigation policies of health shielding.

Figure 19 illustrates the prediction display of diabetes risk.

Figure 20A illustrates the detection of viral particles of H1N1 using a point-of-care device. Figure 20B illustrates the detection of viral particles of H1N1 using a point of care device in clinical samples.

Figure 21 illustrates the detection of host antibodies using a point of care device.

Figure 22A illustrates the detection of host antibodies using a point of care device. Figure 22B illustrates the dynamic range of detection of host antibody using. a point of care device.

Figure 23 illustrates the detection of human cytokine IL-6 using a point-of-care device.

Figure 24 illustrates the detection of protein C and C-reactive protein (CRP) using a point-of-care device in a patient undergoing chemotherapy.

Figure 25 illustrates the detection of glucagon-like peptide-1 (GLP-1) using a point-of-care device.

Figure 26 illustrates the detection of C-peptide, an insulin precursor, using a point-of-care device.

Figure 27 illustrates the detection of C-peptide using a cartridge point-of-care device as compared to a detection system. reference (Lineo).

Figure 28A illustrates the measurement of GLP-1 in three human subjects after feeding. Figure 28B illustrates the measurement of peptide C in the course of the same experiment.

Figure 29 illustrates a calibration curve; which correlates a unit of analysis and a unit of reagents to carry out an analysis regarding VEGFR2.

Figure 30 illustrates the concentration of CRP plotted against the analysis signal (photon count) and the data fitted to a 5-term polynomial function to generate a calibration function.

Figure 31 shows that an adjustment was obtained between a model and the values of the Smax, C0.5 and D parameters as described herein.

Figure 32 shows data according to the dilution used to obtain the final concentration in a test tip.

Figure 33 illustrates the normalized analysis response (B / Bmax) is plotted against the logarithm of the normalized concentration (C / C0.5) for relative dilutions: 1: 1 (solid line), 5: 1 (dashed line) and 25: 1 (dotted line).

Figures 34 and 35 illustrate a similar example as Figure 33 at different normalized concentrations.

Figure 36A shows a projection in IL-6 in septic individuals. Figure 36B shows a decline in protein C in septic individuals.

Figure 37 shows an increase in 11-6 and TNF-a (right panel) in an individual as the burden of HlNl influenza increased in the patient (left panel).

DETAILED DESCRIPTION OF THE INVENTION In one embodiment, the present invention provides "an integrated health data capture, analysis and pandemic mitigation solution, hereinafter referred to as Health Shield (HS) .HS can be used for infection caused by influenza virus and others. pathogenic agents prone to endemic or pandemic spread Influenza outbreaks cost billions of dollars and can not be completely contained by vaccination at this time.The economic losses can be minimized if influenza can be contained by means of a proactive solution that allows administration of effective anti-viral agents and closely targeted quarantines Based on epidemic models, the activation of the HS of the invention can reduce the spreading of the virus, for example, by at least 50%, by means of proactive sampling and containment. "The HS can also reduce the behavior of unnecessary evasion by tracking recreation. and virus in real time. Wherever desired, the test results can be wirelessly relayed to a server that puts the HS programming elements into operation. So, < appropriate entities (for example, local governments, I regional and national) can be notified with alerts when an event is detected, thereby enabling the proactive management of a possible outbreak. In additional modalities, the health armor infrastructure provides strategic industrial and commercial parks as "security zones," which allow for economically important activities to continue. As a result, fewer workers will be infected with the virus and schools and businesses will be less disrupted. Pandemic mitigation strategies will maintain productivity to boost economic growth and impede panic-driven actions.

The system can comprise a set of integrated sampling and modeling technology embedded in a real-time computing infrastructure. The ability to sample, model and learn from data as it is acquired longitudinally, allows the development of an optimal strategy for the care and management of disease on an individual and population basis. Applications on request can be integrated Jipara numerous diseases and therapeutic areas. HS infrastructure can also be used to protect a region from a broad spectrum of threats beyond infectious disease, including chronic disease and threatened by bioterrorism.

I. Health Shield Infrastructure The Health Shield provides a system to contain the spread of infectious diseases through integrated, automated interventions and real-time sampling, modeling, analysis and recommended interventions. For example, the HS can identify active cases in an outbreak (by means of pro-active sampling in high-risk locations)., such as schools or populated commercial areas) and direct the taking of samples and defensive measures, for example, quarantine, of surrounding cases to mitigate or eradicate the outbreak. The HS algorithms characterize the spreading of the epidemic similarly to the case of a. forest fire, where the mitigation policy of the THS models aims to eradicate "hot spots" before a "fire" can take and spread and / or create a firebreak around a hot spot of disease.

In some modalities, the HS comprises two technological components - a field system (FS) and an operating system (OS) - that can be adapted for chronic disease management to improve health outcomes and lower health care costs. (a) Field System (FS) The components of the HS field system can be deployed at various points of care, including, without limitation, a clinic, a community site (eg, school, community center), a hospital, the doctor's office or the individual's home. The FS can also use any number of platforms to monitor the disease, for example, immunoassay, PCR analysis, real-time PCR, microorganism deposition, etc. The FS also includes standard medical equipment, for example, scales to determine weight, blood pressure devices, thermometers to measure temperature, rules to measure height, etc. In some embodiments, the FS devices comprise portable disposable cartridges upon request, as described herein. The FS collects the relevant data in the field and transmits the data to the OS.

In some modalities, the field system comprises a measurement device intended to be deployed in an area to be monitored. In some modalities, FS analyzes samples of body fluid, eg, blood from a finger prick, in real time. The system analyzes body fluids for evidence of infection or disease by detecting, for example, markers of a pathogen. , nucleic acids, proteins, glycoproteins, lipids or a combination of the same indicators of a disease condition. In some embodiments, the FS simultaneously measures multiple markers including one or more of selected antigens or the pathogen, antibodies directed to the pathogen, proteins intracellular or cell surface proteins} or glycoproteins, and cytokines indicative of the response of an infected subject to a given pathogen, (e.g., a 'viral strain or other microorganism). The system can also collect environmental, demographic, personal and physiological information (for example, temperature, blood pressure). In such modalities, such information is collected by means of a graphical contact screen interface. The individualized content can be analyzed by a remote system to facilitate mitigation strategies in real time.

In some embodiments, the FS includes cartridges that perform analyzes on body fluids. The devices include, without limitation, non-significant risk devices and the analyzes can be validated under appropriate guidelines, for example, those provided by the Federal Drug Administration of the United States of America (FDA) and / or International Conference regarding Harmonization ( ICH). The cartridges used by the present invention are described in US patent application No. 11 / 389,409 entitled "POINT-OF-CARE-FLUIDIC SYSTEMS AND USES THEREOF", US patent application No. 11 / 746,535 entitled "REAL-TIME". DETEGTION OF INFLUENZA VIRUS "and US patent application No. 12 / 244,723 entitled" MODULAR POINT-OF-CARE DEVICES, SYSTEMS, AND USES THEREOF "and are described in further detail hereinafter. In some modalities, the only requirement for a FS system is a source of energy for the instruments In other modalities, the source of energy is provided with the FS in the form of a battery, generator, solar power source or other portable power source Cartridges can be pre-loaded with the desired analyzes and require little or no preparation before use, for example, some or all of the components of analysis can be stored in a refrigerator (for example at approximately 4 ° C) before deployment.

The FS platform can put into operation any appropriate analysis that is. currently carried out in the conventional laboratory infrastructure. The new analyzes can be quickly transferred and fully validated. In some modalities, analyzes that are completely new to the HS system can be made upon request and validated within less than about three months, two months, one month, 3 weeks, 2 weeks or less than about 1 week. In some modalities, the analyzes put into operation in the HS systems are validated under the guidelines of the FDA ICH.

Field systems can be placed at any desired point of care, for example, a suspicious area or one known to be at risk of infection or disease. Point-of-care (POCT) tests are defined by a test system near the patient. Exemplary care points include but are not limited to home, clinic, schools or commercial centers. In some modalities, the FS is deployed in mobile units. Thus, it must be understood that medical experts are not necessarily required for testing. To enable this, the FS can be designed to be simple to use and provides all the instructions for use in a simple user interface with a contact screen. In some modalities, the systems are designed by non-literate individuals on computer to test them for themselves in their own homes. In such an installation, data can be sent to a remote system, for example, the operating system as described later in this, where officials or others who monitor the analyzes can learn from the positive test results. In some modalities, the tests and data loading / analysis are carried out in real time in such a way that containment measures can be initiated immediately.

In some modalities, the systems are deployed in public locations. If desired, standard public health employees can be trained to do the tests. In some modalities, the systems are designed in such a way that the total training time is minimized at a given site. For example, the current deployment demonstrates that the training should require no more than half an hour per site, although complementary and advanced training can be carried out as appropriate. In some ? modalities, trained individuals can in turn train others in the use of the systems. The FS can be used successfully in the home by patients who do not have medical training - since the tests are designed to be fully automated and uses a 'graphical contact screen interface on the instrument to hiacer advance the users through the process test. In some embodiments, the only steps required for a user are: 1) to place a sample on the cartridge, for example, sputum or a finger wound can be performed by the user himself using a single lancet. disposable use just as it is used in the management of diabetes for glucose monitoring; and 2) inserting the cartridge to the attached instrument, as described in more detail later herein.

Non-limiting cartridge-on-demand devices i, for use with the FS of the invention are described in U.S. Patent Application No. 11 / 389,409 entitled "POINT-OF-CARE-FLUIDIC SYSTEMS AND USES THEREOF", US Patent Application No. 11 / 746,535 entitled "REAL -TIME DETECTION OF INFLUENZA VIRUS ", and request. US Pat. No. 12 / 244,723 entitled "MODULAR POINT! ^ OF-CARE DEVICES, SYSTEMS, AND USES THEREOF". Such devices are also further detailed hereinafter. (b) Operating System (OS) network often include multiple jumps, for example, an FS device can be connected to a wireless local area network (WLAN) that is securely connected to the World Wide Web by broadband terrestrial lines. l In some embodiments, the operating system includes one or more servers as they are known in the are commercially available. Such servers provide load balancing, task management and backup capacity in the event of failure of one or more servers or other system components, to improve OS availability i. A server can also be implemented in one! distributed network of storage and processor units, as is known in the art, wherein the data processing according to the present invention resides in work stations such as computers. An OS component server can include a database and system processor. A database may reside within the server or may reside on another server system that is accessible to the server. Since the information in a database can contain sensitive information, a security system can be implemented that prevents unauthorized users from gaining access to the database.

In some embodiments, the operating system comprises a data engine that imports data from a desired source to provide instructions regarding epidemic or pandemic mitigation. The OS can translate the source data into a standard format to be analyzed. In some embodiments, the data engine is self-learning and dynamically models a plurality of integrated data sets in real time. This OS modeling procedure provides several benefits. For example, models can be trained to perform a variety of calculations, including but not limited to: 1) predicting results for individuals and populations; 2) quantify the socioeconomic effect of the recommended interventions. In some modalities, the OS is made available to remote users via a remote interface. For example, users can access the OS through a secure online web portal or the like.

The OS programming elements portal incorporates automatic modeling in a system that is constantly learning from each new data point that is transmitted to the portal. programming elements.

By this, the system becomes increasingly more predictive with the passage of time. In some modalities Monte Carlo modeling procedures are used. Monte Cario procedures depend on repeated random sampling to calculate results. The Monte Carlo simulation considers random sampling of probability distribution functions as model inputs to produce hundreds or thousands of possible outcomes instead of a few discrete scenarios. The results provide probabilities that different results will be presented. In some modalities, the solution and readjustment / refinement of model parameter sets is obtained by using reverse lookup techniques and integrated parameter estimation techniques. See, for example, Sheela, 1979 -COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING 19 (1979) 99-106; Moles, et al. 2003 - Genome Res. 2003 13: 2467-2474; Rodríguez-Fernandez, et al. BMC Bioinformatics 2006, 7: 483-500; Barthelmann, et al. 2000 -Advances in Computational athematics 12: 273-288. « There is a rich literature surrounding the modeling and simulation of epidemiological data. The basis of the McKendrick model is a stochastic process (Birth process) that produces a series of differential equations that can be parameterized, explored and inevitably optimized with respect to the control- and spreading of the disease. A reasonably direct analysis of the process is given by Chiang, C.L. 1978. An Introduction to Stochastic Processes and Their Applications. Robert E. Kreiger Publishing Co., Inc. Huntington, NY. p 517. Once the process is established in a stochastic space and expressions appropriately parameterized, explicit, for moments of population and / or probabilities of extinction can be derived. If the process is direct, these expressions can be modeled and estimated either in closed form or numerically.

If populations are large enough that stochastic variation is small compared to global population sizes and system dynamics, the spreading and growth of a disease state can be modeled using systems of differential equations. For example, a simple SIR model (susceptible, infected, removed) of SARS was explored by Choi and Pak, J Epidemiol Community Health. 2003 Oct; 57 (10): 831-5. More complex models that take into account by exposure, the SEIR model, have been explored by d'Onofrio, Matnematical Biosciences 179 (2002) 57-72, especially with respect to the optimization of vaccination strategies. For influenza in particular, Stilianakis, et al., J Infect Dis. 1998 Apr; 177 (4): 863-73, looked at particular aspects of drug resistance in the growth and spread of disease. Other aspects of disease modeling include spreading and diffusion kinetics (FitzGibbon, et al., MATHEMATICAL BIOSCIENCES 128: 131-155 (1995)), mathematical and numerical stability (Dwyer, et al., The American Naturalist, 150 (6) : 685-707; Inaba, J. Mathematics, Biol. (1990) 28: 411-434).

Simulation is a valuable tool in the solution of these complex systems. There are many models' that lend themselves to the solution by simulation. See, for example, Longini, et al., 1984, Int J. Epidemiology. 13: 496-501; O'Neill, 2002. A Tutorial Introduction * to Bayesian Inference for Stochastic Models Using Markov Chain Monte Cario Methods. Math Biosci. 180: 103-114; Gibson, G.J. 1997. Investigating mechanisms of Spatiotemporal Epidemic Spread Using Stochastic Models. Am Phytopathological Society. 87: 139-146. In particular, see Timpka, et al. (2005) AMIA 2005 Symposium Proceedings. 729-733, with respect to influenza simulation. In some modalities, the model of epidemic growth and recreation and the incumbent selection and containment strategies are embedded in an economic • health model of cost-effectiveness. See, for example, Brandeau, et al. Journal of Health Economice 22 (2003) 575-598.

A simplified exemplary model representation in accordance with the invention is shown in Figure 1. The model can be configured to describe spreading, surveillance and mitigation with its concurrent cost effectiveness for the management of epidemic / pandemic policy. Briefly, a population at risk is segmented into several states or conditions (represented by the circles in the figure), with flow components between each state modified by a variety of configurable parameters, including, but not limited to, the infection rate, means and granularity of the monitoring mechanism and the policy decision in hand. To help the politician in the decision process, both out-of-pocket costs and social costs, for example, QALY can be calculated by the model and shown to the politician.

The model illustrated in Figure 1 comprises a system of ordinary non-linear deterministic differential equations. Each node (or state) represents a population of individuals that have characteristics 'Í' phenotypic and similar disease, such as their state of infection. Several states may also represent individuals in different locations, such as schools, workplaces, during hospitalization, isolated quarantine, or isolation at home. A plurality of age groups, for example, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 20, 25, 30, 35, 40, 45, 50 or more age groups,. they are represented by modular structure, thus allowing the specification of age-specific characteristics. In some modalities, the model takes age into account in continuous groups as opposed to discrete groups. The arrows shown * that join the nodes in the figure indicate the flow from one state to another. As described herein, the model parameters come from a variety of sources, eg, literature reports, patient data >; previous outbreaks and can be estimated based on data as desired. The model projections capture a range of possibilities based on the quantified uncertainties. ? As the model predictions are implemented, the parameters can be adjusted continuously in real time according to the actual results in the field. For example, the effectiveness of various mitigation policies can be redefined and adjusted given the real-world results applied to specific affected current populations.

Those skilled in the art will appreciate that the model shown in Figure 1 can be expanded to take into account any number of relevant states and parameters. Figure 2 shows a larger model representation. Each circle represents a class of individual and each arrow represents a transition from one state to another. Transitions from one state to another can take into account changes in natural causes or interventions, for example therapeutic treatment. The model can also take into account transitions that do not involve disease status, for example, changing social interaction with various groups. For example, an individual in quarantine can make the transition from involvement with the community to involvement with a limited number of individuals, for example, contact is limited to health care workers or other health care providers. The model parameters at the beginning of an epidemic can be derived from data from the previous applicable disease outbreak closest to the closest demographics and type of location (for example, a city, a rural area). The model can be continuously refined by applying data gathered within the present epidemic to become progressively better.

Near the top of Figure 2, a flow from left to right is highlighted by the arrow P, Si, Eli, E2i, Ili, I2i, Ri and D ±. These states represent a model of disease spread comprising states of individuals treated prophylactically, for example, with anti-virals (Pi), susceptible individuals (Si), individuals exposed prematurely (El ±), individuals exposed late (E2i), individuals symptomatically infected prematurely (12¿), late symptomatic infected individuals. { I2 ±), recovered-and thus potentially immune-(Pi), and those who died (Di). An individual can make a transition from the E2 ± state to the A state, which represents the asymptomatic infectious sub-population in the community at hand. An individual can also make the transition to state V, which represents vaccination. In the vaccinated state, an individual can transition to either a clear and immune state, or to the ineffective and exposed state, the ±. By taking into account any number of individuals, i, the model can capture a population representation of epidemic recreation. The delay criteria, E2i and? 2 ±, accommodate the spread of the disease dependent on time. The segment above the disease spread model represents the impact of a treatment policy and its effects on the well-being of the population and the spread of disease, while the segment below the specific spread of the disease represents a strategy for mitigating the disease. quarantine. The model integrates an active surveillance strategy, defined by the user and mitigation strategy defined by the user with a cost effectiveness matrix to help in decision making. In some modalities, the model takes into account sub-optimal disease mitigation. For example, even when a hot spot of developing disease has been localized, there may be logistical delays in obtaining therapeutic agents to the area and implementing quarantine. These delays may allow further advancement of the epidemic without mitigation. The model can take into account 'such sub-optimal mitigation.

The model equations form a system of ordinary difference equation (ODE) with appropriately parameterized flow coefficient as defined by the arrows in Figure 2. The basic form of the model is given by the ODE vector: dX / dt = f (X, t) where X is a dimensioned vector and the function f (X, t) is represented by a matrix of mixing parameters and functional interactions as defined in the Figure. In the model in the figure, there are more than 80 dimensions to the dimensioned vector. The skilled artisan will appreciate that the format and components of the matrix for the function f are derivable from Figure 2 and the explanation herein.

The sets of equations represented above are duplicates for each of a variety of age groups, as described in the present. Consider an example with seven age groups. In the example, the conglomerate model of seven sets is replicated for each geopolitical region in a given geographic region. The model can then be generalized to take into account a broader spread of the disease in a larger region. For example, when parameterizing mix matrices and resource / cost tables, interregional and national travel surveillance and mitigation strategies can be taken into account.

A variety of states modeled by the OS and presented in Figures 1 and 2 are shown in Table 1: Table 1: Description and nomenclature for the states used to describe the outbreak The model of the invention can be configured to take into account many characteristics of the individuals, populations and disease that are monitored. In some modalities, the force of infection is taken into account in the model. The force of infection, also called the rate of transmission, refers to the speed at which the existing infectious individuals transmit the disease to susceptible individuals.1 In some embodiments, each infectious individual is given two attributes: a group of age j, based on the age of the individual and a mix group k, based on the mix pattern in society. Blending patterns include without limitation freely with others in society, for example, in school or work, reduced mix of taking days off from work due to illness, etc. The force of infection exerted on the population age group i by all populations of age group j can be calculated as follows: where, ß is transmission speed (per day per infectious individual per susceptible individual) T is a parameter that defines the randomness of mixing between different age groups: yes? = 1 the interactions are perfectly assorted, if T = 0, the interactions are perfectly random Pi is the relative susceptibility of individuals in the age group i < Pi is the relative infection capacity of infectious individuals of the age group j Ak ± j is a weighting factor that takes into account differences in the relative extent of interactions that potentially cause transmission between individuals of age group i and those of age groups j and mixing groups k Ikj is the number of infectious individuals in the age group j _? * 7 is the total number of individuals of age group j and mix group k in the population Nt is the total number of individuals of groups of all ages in the population In the infection force equation, the Ak ± j interaction weights are calculated based on 1. the time spent by an individual of the age group i in the company of individuals of age group j and the group of mixture k in different places such as work, school, house, etc. 2. the number of individuals from age groups j and mix group k who come into contact that potentially causes transmission with an individual of age group i From the above parameters, p3, (¾, Akij, N * ^, can change dynamically over time as a result of the evolution of the epidemic, the imposition of mitigation policies, or both.

The OS model may include a number of mitigation policies that direct the medical decision-making policy when faced with an outbreak. These policies can be modeled for each particular facility, for example, geographic location and disease or infectious agent, to take better advantage of the available resources. Each policy can be imposed with an efficiency / compliance list that can be estimated from historical data. The model can predict the results of implementing various mitigation policies, thereby providing the appropriate individuals with a suggested response. Exemplary non-limiting mitigation policies are listed in Table 2: Table 2: Mitigation Policies Represented in the Model In addition to the mitigation policies, the OS model can incorporate results obtained in the field when surveillance is carried out with a variety of different technologies. These include the cartridge systems described herein, rapid antigen test, immunofluorescence, immunoassay, real-time PCR, viral culture test, physiological measurements, urine and blood work, etc. The model includes the representation of the sensitivity and specificity of each test for samples from both asymptomatic individuals and symptomatic individuals. In addition, the stopping time for the different tests can be included in the model.

Depending on each particular system, several forms of surveillance strategies can be included in the model. In one modality, surveillance comprises the evidence of individuals reporting. for tests voluntarily. Surveillance can also be carried out by population groups that include but are not limited to the following: • Children between 1-4 years of age • Children between 5-14 years of age • Pregnant women • Young adults between 15-30 years of age • Frontline medical response workers • Individuals identified at high mortality risk | • Geriatric • Individuals of average age between 30-60 years of age Each of these population groups can be tested using any of the test methods or combinations thereof. Different proportions of asymptomatic individuals and symptomatic individuals who voluntarily report for tests can also be: taken into account in the model.

In another modality, surveillance includes testing based on the implementation of any surveillance policy as defined by the end user. The catalog of surveillance policies captured by the model includes, without limitation, the following: · Domestic surveillance: whole house tests based on the case confirmed by index • School monitoring: tests of school children based on the case confirmed by index • Surveillance of the workplace: employee tests based on the case confirmed by index For confirmed cases identified as a result of surveillance tests, appropriate quarantine, prophylaxis, or hospitalization action may be taken.

In some modalities, the HS allows an automated analysis to be carried out using these methodologies for the selection, parameterization and / or exploration of an appropriate epidemic model to implement the optimal selection and contention strategy. The model can be modified according to a model of health economics of cost effectiveness. In some embodiments, the model is configured to predict spread of an infectious pathogen in one. heterogeneous human population .. Models can take into account regional demographic factors and individual risk factors. As described in more detail later herein, in one embodiment, the model allows the evaluation of health care mitigation policies, including without limitation: a) surveillance / test strategies; b) hospitalization, isolation at home and quarantine policies; c) prophylactic vaccination policies and treatment, for example, anti-viral therapy; and d) social distancing measures such as closure. of schools and places of work.

In addition to the dynamics of the infectious outbreak, the model can provide the cost determination also as an assessment of the adjusted quality of life years (QALY) saved by comparing alternative mitigation procedures. The model can be configured to take non-economic cost measures into account. The model can be configured to adjust the cost with different errors, based on economic cost, temporary costs or other factors, in order to minimize the cost of errors made by a model. For example, the model can assign a high cost to the bad diagnosis of an infected individual in such a way that mitigation strategies are not put in place. The model could then be adjusted to favor evasion of such factors. Similarly, a bad diagnosis by chronic condition can have a lower cost since the individual can be tested again before the disease has advanced enough. epidemic, predictions may not only relate to the individual case, but to populations of people in different regions. Based on large sets of demographic data, the HS analytical system can be configured to predict risk and optimized costs for both treatment and analysis management. For example, the locations with the lowest expected risk can be sampled less than the locations with the highest expected risk.

The OS has integrated actions that are triggered when certain events are detected. For example ^ alerts can be sent to government officials when an infected individual is detected. Rules can be adjusted to notify a clinician automatically by phone, email or facsimile when a case is detected. The individual detected and contacts, for example, family members, collaborators or anyone who has had contact with the individual in the past few days, weeks, months or years, may also be notified. The rules that trigger the action can be made before deployment or during a monitoring period depending on the needs of the situation.

The OS models also perform hygiene checks and disperses on the data received from the FS. In some modalities, actions are taken when variability or noise is identified in the data. In some modalities, an analysis for an individual is repeated when scattered values are detected.

In some modalities, OS models can predict outcomes for individuals and populations. In some modalities, the models match predictions - such as response to infection, optimal treatment regimen for an individual or population and projected spread: of the virus - with real historical data, eg, data from the spring influenza season. In some modalities, the models consider the effectiveness of strategies; of intervention proposals for individuals and populations, including the use of pre-emptied anti-viral therapies, reactive anti-viral therapies, quarantine, hospitalization, targeted closures and establishment of "safe zones" in key hotels, restaurants, schools, manufacturing plants and other locations. The models can also quantify the socioeconomic effect (out-of-pocket expenses, lives saved, lost days of productivity, etc.) that the recommended interventions would have had at the time of each case.

In some modalities, field and OS systems are also tailored to provide solutions for various installations where systems can improve! the results and reduce the cost of care. For example, FS and OS can provide health monitoring solutions for pharmaceutical and biotechnology companies and for consumers.

II. Deployment of the Health Shield In some modalities, the Health Shield comprises a fully integrated diagnostic / patient health record / electronic medical record platform. The deployed field system devices can be configured to be portable and thus can be deployed at a variety of care points, including without limitation a clinic, a community site (eg, school, community center), a hospital, the doctor's office or the individual's home. As described herein, portable FS devices can be configured to connect wirelessly to a network, requiring only an optional cable for power. In some modalities, the network connection is made to a web portal where analysis data are sent in real time. FS systems can be deployed in urban environments near care centers and the same devices can be deployed in remote facilities, for example, even where patients live long distances from the nearest medical clinic.

The performance of FS analysis will vary from analysis to analysis but all tests are developed with the objective of high accuracy, for example, via high specificity and sensitivity. In some modalities, the specificity is greater than approximately 50%, 55%, 60%, 65%, 70%, 75%, 80%, 85%, 90%, 91%, 92%, 93%, 94%, 95 %, 96%, 97%, 98% or greater of approximately 99%. In some modalities, the specificity approaches 100%. In some modalities, the sensitivity is greater than approximately 50%, 55%, 60%, 65%, 70%, 75%, 80%, 85%, 90%, 91%, 92%, 93%, 94%, 95 %, 96%, 97%, 98% or greater of approximately 99%. In some modalities, the sensitivity approaches 100%. The exact performance of an analysis may depend on a variety of factors, including but not limited to the performance of the marker that is detected, the user's ability and performance of analysis inherent in the device. In some modalities, FS systems are designed to be highly compatible with the user and require minimal ability to operate effectively. The time required for the performance of the analysis will also vary based on the use case for deployment. Each system is fully tailor made to better achieve the deployment objectives in such a way that all specifications are adjusted accordingly. In some embodiments, the analyzes are put into operation in a matter of minutes, for example, less than about 30 minutes, 25 minutes, 20 minutes, '15 minutes, 10 minutes, 9 minutes, 8 minutes, 7 minutes, 6 minutes, 5 minutes, 4 minutes, 3 minutes, 2 minutes or less of approximately 1 minute. In some modalities, the HS exceeds the current centralized laboratory test analyzes through extensive test intervals.

The analyzes of the present invention can advantageously examine a set of markers. In some modalities, the tests will measure both antibodies against the viral load to provide an improved assessment of the status of an individual subject. The analyzes may also be designed to measure other markers of infection and response to infection, for example, levels of cytokine production and will therefore provide additional information about the severity of the disease, suggest individualized treatments and may also indicate when confirmatory tests are appropriate for a negative initial selection.

The system may also be configured to detect infection with mutant strains or other strains that are not yet characterized. Before those strains are identified, projections on inflammatory markers may indicate that an individual is infected, with a strain that has not yet been identified, thereby allowing a potential rapid containment and identification of the fact that the virus is mutating. Defensive measures (such as investments in vaccinations) can then be updated accordingly.

The HS technology is configurable to be simple to use and eliminates multiple stages for the analysis of data samples that would otherwise be presented under existing situations (eg, sample collection, packaging, remote analysis, decisions). As a result, the HS can provide greater accuracy and faster decision by providing field data in real time to a central monitoring site, for example, that of a government agency. The system provides through this the opportunity of support and direction of optimal health care. For example, FS systems can be located at community friendly sites, such as pharmacies, schools, clinics or recreation centers, so that citizens could easily be tested and / or treated on a desirable basis, for example , to monitor infectious diseases such as influenza. In addition, because the device can be portable, community workers can visit the elderly and others unable to travel or make home visits when infection is suspected, for example, due to influenza. In some modalities, the collected data are analyzed based on the individual and population circumstances. These analysis data collected by the FS devices deployed can be made available to suppliers, government officials, hospitals or the like.

When deployed in a region of interest, for example, a school, community center, commercial center, local, regional or nationally, the HS can be used to develop security systems for the monitoring of potential adverse events and pandemics of care Health. The FS device can also be used in high selection strategies where a large number of individuals, for example, anyone at risk or suspected of being at risk, can be tested on a routine basis in a preventive manner or in reaction to a outbreak. The data collected by the FS is accumulated in the OS, which then adds and manages the collective data. In some embodiments, the system requires only a small sample of body fluid, for example, a finger prick of blood, saliva or sputum, peak safety issues arising from the extraction of blood are extensively reduced or eliminated. In some modalities, real-time data is used to help select the optimal biomarker analyzes for a given situation. In some modalities, the set of analytes is prospectively chosen as a subset of a large analysis menu. Thus, the set of ideal analyzes appropriate for the premature stage of an epidemic (which could emphasize the detection of antigen) can be changed later in the epidemic, for example, to look for antibodies that provide information as to the probable stage of immunity of the community that may be relevant to the management of subsequent epidemics.

When infectious disease is monitored, the Health Shield deployment strategy can provide selection and sampling for the population at risk derived from the minimum number of initial outbreaks expected. In some modalities, 'the system assumes the same range of cases that have occurred to provide real-world empirical data for modeling the spread of the disease.

An index case can potentially infect any number of secondary individuals. The number of secondary individuals may depend on any number of factors in the index case, including but not limited to age, mobility, life situation, work environment, socialization, and geographic location. The HS can model these and other factors to estimate the potential spread of a given outbreak. In a non-limiting example, real-world data suggest that a typical index case is likely to infect 50 other - individuals. An exemplary pattern of infection may include 4 or 5 family members and 45 or 46 collaborators, friends and other people with whom the infected person has contacted. In the HS rapid response model, each index case would require 25 to 50 secondary selections (regardless of age group) to prevent people in contact with the index case from becoming infected and spreading the virus. Depending on the characteristics of the index case and infectious agent, 5, · 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95 or 100 secondary selections may be required. In some modalities, more than 100 secondary selections may be necessary for an index case.

In some embodiments, the HS is equipped with an initial quantity of FS device cartridges,. for example, approximately 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 30, 40, 50, 60, 70, 80, 90 or 100 times the expected number of index cases. In some modalities, the system provides approximately 50 times the number of cartridges per expected number of index cases. Each cartridge can be used to test a sample of body fluid, as described herein. The abundance of cartridges provides a proactive containment on demand for pandemic mitigation. Once the infrastructure is activated, the HS provides boarding on additional demand as required. · This scheme provides selection and sufficient sampling to cover the population at risk that surrounds index cases.

Individuals can be provided with a device when seeking a prescription for drugs by any of the common methods, for example, in a pharmacy. The individual can be given a device in a school, workplace or other area of interest; The devices can also be manually distributed :! by health care workers. When the device is distributed to an individual, the contact information1: of the individual, including without limitation, cell phone, email address, text message address or other wireless communication means, may at that time be entered into the bases of data, of the OS component and associated with the individual in the same. The OS system may include a script or other program ::: which can detect when a signal generated from a detection device has not yet been sent to the OS system, for example at a given time and the OS system can then send an alert notifying the individual to test a sample of body fluid.

Due to the portability and size of the FS components of the Health Shield, the HS can become part of the daily lifestyle to manage disease and potential health hazards. In some i modalities, the systems are placed in homes and in easily available locations. The collection of data in ? Real time and data analysis provide a rapid pro-active health care system to respond to sudden risks. i HS systems can predict optimal surveillance measures for disease management. The system of HS can identify outbreaks as early as possible to track and contain the spread to allow for appropriate, rapid mitigation strategies to be put in place. The model for a given installation can; be optimized to take into account several factors to provide optimal surveillance and mitigation strategy. A faculty member includes prioritizing tests based on ri'esgo factors i and symptoms, including giving priority to infant tests, ? children, pregnant women, medical personnel, high-risk individuals and geriatrics. Another factor, includes testing close contacts of index cases, such as pointing home tests, schools and workplaces where there are confirmed or suspected cases. In addition, the system can determine the impact of alternative diagnostic tests based on several factors specificity, stop (this results of an analysis). performed analyzes comprise one or more of cartridge analysis1, real-time PCR, rapid antigen tests, viral cultures and immunoassays. In some modalities;, a less expensive analysis can be used for a large number of secondary analyzes to minimize expenses. Based on these data, a smaller number of more expensive analyzes, ii J. but more sensitive and specific can be used to test selected individuals.

When suspected infected individuals are detected by the HS, whether the individual is symptomatic or asymptomatic, field tests can be performed with the FS and the results and location of the subject can. be released to the OS, for example, on a central server to a central monitoring site. At the monitoring site, results can be displayed and alerts recorded if appropriate in such a way that containment efforts, including additional deployment and testing of FS components, can be initiated. In some modalities, the model contained in the programming elements will automatically suggest where the disease is likely to spread and where resources will be needed to be deployed to contain the disease and monitor in the additional field. The system can be put in contact with individuals involved in the. surveillance, for example, government or health care workers, for example, by telephone, pager, facsimile, email, text message or other form of rapid communication. In some modalities, the data and analyzes provided by the HS are provided to health care professionals and professionals, not to individual users. This helps ensure that medical decision-making is done appropriately. í An advantage of the Health Shield as described herein is that the results of the analysis of the field systems can be communicated substantially immediately to any third party who can benefit from obtaining the results. For example, once * the results of a measurement taken by a device FS are communicated to the OS, it can be determined: an analyte concentration in the operating system component and transmitted to an individual or medical personnel who may need to take additional action. This could include identification of an index case. The phase'! communication to a third party may be effected wirelessly as described herein and; When transmitting the data to a portable device of the third party, the third party can be notified of the analysis results virtually at any time and in any place. Thus, in a time-sensitive setting, the patient can be contacted immediately if urgent medical action may be required. ? The systems of the invention may be designed to interface with any combination of different Electronic Health Record (EHR) systems and any other relevant databases. In addition, the system can be configured to automatically translate data that currently exists in different formats into a standard format. Once the system imports and translates the data, it can centralize the information in one or more repositories and pass the imported data through predictive models. In this way, the system can compile and take advantage of multiple data sources to better model the outbreak and predict appropriate containment responses. Those models learn from each new data point, becoming increasingly predictive over time. In some modalities, models recognize patterns that predict how a given disease of the individual is likely to advance.

A pilot program can be used to help refine system parameters. In some modalities, an initial selection and containment strategy is developed. Then the HS is deployed to direct that model in a region of interest, for example, a town, neighborhood, hospital or commercial area. With this pilot the robustness of the assumptions underlying the modeling effort can be tested and the containment strategy can be fine-tuned. In some modalities, the fine adjustment is carried out automatically by the learning algorithms of the OB. For example, the modeling programming elements contain pattern recognition technologies that allow the algorithms to predict the spread of the disease to be continually refined with each new data point sent to the portal of the elements of programming elements. As such, the system becomes increasingly predictive with the passage of time. In some modalities, these refinements continue even after the system is deployed after the pilot stages.

After a system is developed using historical data, archived samples and even the pilot phase, the systems can be placed at strategic sites to begin to prevent the spreading of any outbreak. Because each instrument can process different cadges that can be custom-made for a given disease of interest, for example, with a specific influenza strain of concern, the same systems can be used to contain and prevent the spread of a disease. virus still mutates. In some embodiments, the cadges contain protein-based tests that measure inflammation and response to infection allowing officials to recognize severe infection even if the virus mutates and specific tests for new viral strains can be immediately developed and deployed through the existing infrastructure and instruments. further, the same instruments deployed to monitor infectious disease are available to then monitor other health-related issues such as diabetes, obesity, cardiovascular disease and oncology concerns, for example, cancer therapy. Different cartridges and additional models for the programming elements can be made on request around HS systems already in place. Validation data for each application can be made before deployment and adjusted prospectively by learning the incoming data.

Non-compliance with the recommended treatment may undermine the effectiveness of the containment strategy of the present invention. As such, in some embodiments, the system of the present invention can be used to monitor patient compliance and notify the patient or other medical personnel of such non-compliance. For example, a patient who takes a pharmaceutical agent as part of the medical treatment plan may take a sample of body fluid which is analyzed as described herein, but a concentration of the metabolite, for example, detected by the system may be a high level compared to a known profile that will indicate multiple doses of the pharmaceutical agent have been taken. The patient or medical personnel may be notified of such non-compliance via any method discussed herein, including without limitation notification via a portable device such as } a PDA or cell phone or through a third party such as a health care worker who also receives communication of noncompliance. Such known profile may be located or stored in an external device described herein.

In one embodiment, the system can be used to identify sub-populations of patients who are benefited or damaged by therapy. In this way, drugs with potential toxicity can be administered to only those who will benefit.

In terms of pharmaceutical-related adverse events, Health Shield systems can be placed in the residence of an individual. In some modalities, HS is used to monitor the safety and efficacy of treatments for acute conditions, for example, debilitating or life-threatening illness or chronic conditions. FS components can also be placed in central locations such as pharmacies in such a way that individuals can be tested when they fill prescriptions.

Case studies have been conducted for diabetes, infection and oncology considering the needs of government disease management systems as well as health care corporations. One such study was aimed at a model to prevent and reverse diabetes. The modeled data demonstrated significant cost savings associated with the elimination of centralized infrastructure for blood and analysis of health information data and instead using the systems of the present invention with FS systems placed at various care points, including the home environment The system provided savings in part by limiting packaging costs, reducing personnel costs associated with commissioning analysis, reducing costs associated with false positives, reducing time associated with expected results. In several modeling environments, the HS system would reduce the costs associated with conventional tests by more than an estimated 50%, in addition to the value of time saved in acquiring the relevant data. 5. Monitoring of Influenza Outbreaks In one aspect, the systems of the invention are deployed to monitor and contain outbreaks of disease. HS is particularly beneficial in the adjustment of influenza because the containment strategies that initially depend on mass vaccination programs may not be effective enough to contain an outbreak. Strains of influenza A virus are classified according to two proteins found on the surface of the virus: haemagglutinin (H) and neuraminidase (N). All influenza A viruses contain these two surface proteins, but the structures of these proteins differ between strains of viruses due to the rapid genetic mutation in the viral genome. There are 16 H subtypes and 9 known N subtypes in birds, but only a subset, for example, H l, 2 and 3, and N 1 and 2, are commonly found in humans. The pathogenicity of a strain varies between subtypes. For example, the H5N1 strain, commonly referred to as "avian influenza" or "bird flu", most commonly affects birds but a recent outbreak of the strain in humans in Asia killed up to 60% of those infected.

Although influenza vaccines can help prevent recreation, the changing subtypes and mutations of influenza make vaccination only a partial solution. For example, the HlNl influenza virus, commonly referred to as swine influenza, is responsible for the 2009 pandemic. Like H5N1, HlNl can be virulent in humans. The Center for Disease Control and Prevention (CDC) of the United States of America maintains information about the 2009 HlNl pandemic at www.cdc.gov/HlNlFLU/. The CDC is concerned that the new H1N1 influenza virus could result in a particularly severe flu season in 2009, for example, through widespread illness, doctor visits, hospitalizations and deaths. The first H1N1 vaccine will not be available before mid-October to the first ones and sufficient vaccine supply will not be enough to treat even the most at-risk populations until later in the summer. As a result, the best way to prevent a widespread epidemic and panic from the public will be to control the virus to prevent its spread, particularly to those who are at higher risk.

Some governments have tried methods of influenza containment that were effective with severe acute respiratory syndrome (SARS), including selecting for fever or respiratory symptoms. However, these methods are not sufficiently targeted to contain H1N1. One problem is that influenza victims can be contagious at least one day before a fever or other symptoms arise. In some embodiments, the Health Shield of the invention systematically tests not only those who are symptomatic but also family members and close work associates. Thus, infected individuals can be treated and isolated before they have the opportunity to spread the infection widely, reducing the real and psychological impact of influenza.

The spread and proportion of influenza deaths in the fall of 2009 would be mitigated by preventing patients from flooding emergency rooms for testing and treatment. Potentially hundreds of millions of dollars can be saved by reducing visits to the emergency room and expensive hospitals, by appropriately using medication or by reducing the spread of the virus in hospitals. The HS models of the invention can identify optimal intervention strategies and synchronization for administration of appropriate medication, such as Tamiflu. These stages can reduce visits to the hospital and emergency room and allow people to resume work more quickly. Eliminating such unnecessary visits to the emergency room can help prevent the spread of the virus and reduce hospitalization and expenses. emergency rooms.

Influenza, for example, H1N1 and H5N1, can be detected from a body fluid, for example, a finger prick of blood, sputum, saliva, or a combination thereof, using FS point of care instruments. These instruments can be placed in appropriate locations (for example, homes, schools, restaurants, primary care units, livestock facilities, etc.) and can be deployed in many cases without local support infrastructure other than an energy source. The tests can be done quickly, for example, in less than about 1, 2, 3, 4, 5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55 or 60 minutes. In some modalities, FS results are reported in response to a central OS monitoring site in real time. Blood or saliva-based assays can detect influenza by using several methods, including immunodetection using antibodies sensitive to specific epitopes. example, hemagglutinin and / or neuraminidase. The distinguish between the various types of influenza strains identified, for example influenza A, influenza B, H5N1, H1N1, etc. The analyzes can detect individual particles of a particular virus strain, even in a background = f.

I1 of different strains or genetic variants. The analyzes can detect biomarkers, viral proteins, coating proteases and the like. j In some modalities, the tests measure inflammatory markers and response markers for example, cytokines, which allow the clinicians to identify the severity of infection, the extension of the acute phase and / or inflammatory reactions of the subject, testo can help, for example, in determining appropriate treatment for an individual. The measuring the response to infection allows characterization There are currently more than 100 cytokines / chemokines whose coordinated or discordant regulation is of clinical interest. Exemplary cytokines that can be used in the systems and methods of the invention include, but are not limited to, BDNF, CREB pS133, Total CREB, DR-5, EGF, E A-78, Eotaxin, fatty acid binding protein , FGF-basic, granulocyte colony stimulating factor (G-CSF), GCP-2, granulocyte-macrophage colony stimulating factor GM-CSF (GM-CSF), oncogenic-growth-related keratinocytes (GRO-KC), HGF, ICAM-1, IFN-alpha, IFN-gamma, the interleukins IL-10, IL-11, IL-12, IL-12 p40, IL-12 p40 / p70, IL-12 p70, IL-13, IL -15, IL-16, IL-17, IL-18, IL-lalpha, IL-lbeta, IL-lra, IL-Ira / IL-1F3, IL-2, IL-3, IL-4, IL-5 , IL-6, IL-7, IL-8, IL-9, interferon-inducible protein (10 IP-10), JE / MCP-1, keratinocytes (KC), KC / GROa, LIF, Lyfotacin, M- CSF, monocyte chemoattractant protein-1 (MCP-1), MCP-1 (CAF), MCP-3, CP-5, DC, IG, inflammatory macrophage (MIP-1 alffa), IP-1 beta, IP-1 gamma, MIP-2, IP-3 beta, OSM, PDGF-BB, T cell expressed and secreted normal r egulated after activation (RANTES), Rb (pT821), Rb (total), Rb pSpT249 / 252, Tau (pS214), Tau (pS396), Tau (total), tissue factor, tumor necrosis factor-alpha (TNF-alpha), TNF-beta, TNF-RI, TNF-RII, VCA-1, and VEGF. In some embodiments, the cytokine is IL-12p70, IL-10, IL-1 alpha, IL-3, IL-12 p40, IL-Ira, IL-12, IL-6, IL-4, IL-18, IL -10, IL-5, eotaxin, IL-16, MIG, IL-8, IL-17, IL-7, IL-15, IL-13, IL-2R (soluble), IL-2, LIF / HILDA, IL-1 beta, Fas / CD95 / Apo-1, and MCP-1.

Flammable markers that can be used with the systems and methods of the invention include ICAM-1, RANTES, MIP-2, β-1-beta, α-1-alpha, and MMP-3. Additional markers of inflammation include adhesion molecules such as integrins αβ, α2β1, α3β1, 4β1, α5β1, adβ ?, a7β1, a8β1, a9β1, aβ7, a4β7, a6β4, β2, a1, β2 , a? ß2, a? ß3,? ß5, a? ß6, a? ß8, a? ß2, a? ß3, a?? ß7, integrin beta-2, integrin beta-3, integrin beta-- 2, beta-4 integrin, beta-5 integrin, beta-6 integrin, beta-7 integrin, beta-8 integrin, alpha-i integrin, alpha-2 integrin, alpha-3 integrin, alpha-integrin -4, alpha-5 integrin, alpha-6 integrin, alpha-7 integrin, alpha-8 integrin, alpha-9 integrin, alpha-D integrin, alpha-L integrin, alpha-M integrin, alpha-v integrin , integrin alpha-- ?, integrin alpha-IIb, integrin alphalELb; integrin-associated molecules such as Beta IG-H3, Melusin, CD47, MEPE, CD151, Osteopontin, IBSP / Sialoprotein II, RAGE, IGSF8; selectins such as E-selectin, P-selectin, L-selectin; and ligands such as CD34, GlyCAM-1, MadCAM-1, PSGL-1, vitronectic, vitronectin receptor, fibronectin, vitronectin, collagen, laminin, ICAM-1, ICAM-3, BL-CAM, LFA-2, VCA - 1, NCAM, and PECAM. Additional markers of inflammation include cytokines such as IFN-a, IFN-β, IFN-e, -, - T, and - ?, IFN- ?, IFN- ?, IL29, IL28A and IL28B, IL-1, IL-? a and b, IL-2, IL-3, IL-4, IL-5, IL-6, IL-7, IL-8, IL-9, IL-10, IL-11, IL-12, IL-13 / IL-14, IL-15, IL-16, IL-17, IL-18 ,. IL-19, IL-20, IL-21, IL-22, IL-23 ,. IL-24, IL-25, IL-26, IL-27, IL-28, IL-29, IL-30 and TCCR / WSX-1. Additional markers of inflammation include cytokine receptors such as common beta chain, IL-3 R alpha, IL-3 R beta, GM-CSF R, IL-5 R alpha, common gamma chain / IL-2 R gamma, IL-2 R alpha, IL-9 R, IL-2 R beta, IL-4 R, IL-21 R, IL-15 R alpha, IL-7 R alpha / CD127, IL-lra / IL-lF3, lI-l R8 , IL-1 RI, IL-1 R9, IL-1 RII, IL-18 R alpha / IL-1 R5, tlL-1 R3 / IL-1 R AcP, IL-18 R beta / IL-1 R7, IL -1 R4 / ST2 SIGIRR, jlL-1 R6 / IL-1 R rp2, IL-11 R alpha, IL-31 RA, CNTF R alpha, Leptin R, G-CSF R, LIF R alpha, IL-6 R, OSM R beta, IFN-alpha / beta; RI, IFN-alpha / beta R2, IFN-gamma RI, IFN-gamma R2, IL-10 R alpha, IL-10 R beta, IL-20 R alpha, IL-20 R beta, IL-22 R, IL- 17 R, IL-17 RD, IL-17 RQ, IL-17B R, IL-13 R alpha 2, IL-23 R, IL-12 R beta 1, IL-12 R beta 2, TCCR / WSX-1, and IL-13 R alpha 1. Additional markers of inflammation include chemokines such as CCL-1, CCL-2, CCL-3, CCL-4, CCL-5, CCL-6, CCL-7, CCL-8, CCL- 9, CCL-10, CCL-11, CCL-12, CCL-13, CCL-14, CCL-15, CCL-16, CCL-17, CCL-18, CCL-19, CCL-20, CCL-21, CCL-22, CCL-23, CCL-24, CCL-25, CCL-26, CCL-27, CCL-28, MCK-2, MIP-2, CINC-1, CINC-2, KC, CINC-3, LIX, GRO, Timo Chemokine-1, CXCL-1, CXCL-2, CXCL-3, CXCL-4, CXCL-5, CXCL-6, CXCL-7, CXCL-8, CXCL-9, CXCL-10, CXCL -11, CXCL-12, CXCL-13, CXCL-14, CXCL-15, CXCL-16, CXCL-17, XCL1, XCL2, and quemerin. Additional markers of inflammation include chemokine receptors such as CCR-1, CCR-2, CCR-3, CCR-4, CCR-5, CCR-6, CCR-7, CCR-8, CCR-9, CCR-10, CXCR3, CXCR6, CXCR4, CXCR1, CXCR5, CXCR2, Chem R23. Further markers of inflammation include tumor necrosis factor (TNF), such as TNFa, 4-1BB ligand / Tnfsf9, LIGHT / TNFSF14 APRIL / TNFSF13, Lymphotoxin, BAFF / TNFSF13B, Lymphotoxin beta / TNFSF3, CD27 ligand / TNFSF7, ligand OX40 / TNFSF4, CD30 ligand / TNFSF8, TL1A / TNFSF15, CD40 ligand / TNFSF5, TNF-alpha / TNFSFlA, EDA, TNF-beta / T FSFlB, EDA-A2, TRAIL / TNFSF10, Fas ligand / TNFSF6, TRANCE / TN SF11, GITR Ligand / TNFSF18, and T EAK / TNFSF12. Further markers of inflammation include receptors such as TNF superfamily 4-1BB / TNFRSF9, NGF R / TNFRSF16, BAFF R / TNFRSF13C, Osteoprotegerin / TNFRSFllB, BCMA / TNFRSF17, OX40 / TNFRSF4, CD27 / TNFRSF7, RANK / TNFRSF11A, CD30 / TNFRSF8, RELT / TNFRSF19L, CD40 / TNFRSF5, TACI / TNFRSF13B, DcR3 / TNFRSF6B, TNF RI / TNFRSF1A, DcTRAIL R1 / TNFRSF23, TNF RII / TNFRSF1B, DcTRAIL R2 / TNFRSF22, TRAIL R1 / TNFRSF10A, DR3 / TNFRSF25, TRAIL R2 / TNFRSF10B, DR6 / TNFRSF21, TRAIL R3 / TNFRSF10C, EDAR, TRAIL R4 / TNFRSF10D, Fas / TNFRSF6, TROY / TNFRSF19, GITR / TNFRSF18, TWEAK R / TNFRSF12, HVEM / TNFRSF14, and XEDAR. Additional markers of inflammation include regulators of the TNF superfamily such as FADD, TRAF-2, RIP1, TRAF-3, TRADD, TRAF-4, TRAF-1, and TRAF-6.

Additional markers of inflammation include acute phase reagents and acute phase proteins. Additional markers of inflammation include ligand of the TGF-beta superfamily such as Activin, Activin A, Activin B, Activin AB, Activin C, BMP (bone morphogenetic proteins), BMP-2, BMP-7, BMP-3, BMP -8, BMP-3b / GDF-10, BMP-9, BMP-4, BMP-10, BMP-5, BMP-15 / GDF-9B, BMP-6, Decapentaplegic, growth / differentiation factors (GDF), GDF-1, GDF-8, GDF-3, GDF-9 GDF-5, GDF-11, GDF-6, GDF-15, GDF-7, ligands of the GDNF family, Artemin, Neurturin, GDNF, Persefin, TGF-beta, TGF-beta, TGF-beta 3, TGF-beta 1, TGF-beta 5, LAP (TGF-beta 1), latent TGF-beta bpl, latent TGF-beta 1, latent TGF-beta bp2, TGF -beta 1.2, latent TGF-beta bp4, TGF-beta 2, Lefty, MIS / AMH, Lefty-1, Nodal, Lefty-A, Activin RIA / ALK-2, GFR alpha-l / GDNF R alpha-1, Activin RABBIT / ALK-4, GFR alpha-2 / GDNF R alpha-2, Activin RIIA, GFR alpha-3 / GDNF R alpha-3, Activin RIIB, GFR alpha-4 / GDNF R alpha-4, ALK-1, MIS RII, ALK-7, Ret, BMPR-IA / ALK-3, TGF-beta RI / ALK-5, BMPR-IB / ALK-6, TGF-beta RII, BM PR-II, TGF-beta Rllb, Endoglin / CD105, and TGF-beta RUI. Additional markers of inflammation include modulators of the TGF-beta superfamily such as Amnionless, NCAM-1 / CD56, BAMBI / NMA, Noggin, ??? - 1 / PCP, NOMO, Charon, PRDC, Cerberus 1, SKI, Cordin, Smadl, similar to cordina-1, Smad2, similar to Chordina-2, Smad3, COCO, Smad, CRIM1, Smad5, Crypto, Smad7, Crossveinless-2, Smad8, cryptic, SOST, DAN, latent TGF-beta bpl, Decorin, Latent TGF-beta bp2, FLRG, latent TGF-beta bp4, Folistatin, T EFFl / Tomoregulin-1, similar to · follistatin-1, TMEFF2, GASP-1 / FIKKNRP, TSG, GASP-2 / FIKKN, TSK, Gremlin and Vasqrin. Additional markers of inflammation include EGF ligands such as Anfiregulin, LRIG3, Betacellulin, Neuregulin-1 / NRG1, EGF, Neuregulin-3 / NRG3, Epigen, TGF-alpha, Epiregulin, TMEFFl / Tomoregulin-1, HB-EGF, TMEFF2, and LRIG1. Additional markers of inflammation include the EGF R / ErbB receptor family, such as EGF R, ErbB3, ErbB2 and ErbB4. Additional markers of inflammation include fibrinogen. Additional markers of inflammation include SAA. Additional markers of inflammation include glial markers, such as alpha .1-antitrypsin, C-reactive protein (CRP), a2-macroglobulin, glial fibrillary acid (GFAP) protein, Mac-1 and F4 / 80. Additional markers of inflammation include myeloperoxidase. Additional markers of inflammation include complement markers such as C3d, Clq, C5, C4d, C4 bp and C5a-C9. Additional markers of inflammation include major histocompatibility complex (MHC) glycoproteins, such as HLA-DR and HLA-A, D, C. Additional markers of inflammation include microglial markers, such as CR3 receptor, MHC I, MHC II, CD31, CDlla, CDllb, CDllc, CD68, CD4, 5RO, CD45RD, CD18, CD59, CR, CD45, CD64 and CD44. Additional markers of inflammation include alpha 2 macroglobulin receptor, fibroblast growth factor, Fe gamma RI, Fe gamma RII, CD8, LCA (CD45), CD18, CD59, App J, ? clusterin, plasminogen activator inhibitor type 2, CD44, macrophage colony stimulating factor receptor, MRP14, 27E10, conjugates of 4-hydroxynonenal- 'protein, ???, NF B, cPLA 2, COX-2, metalloproteinases of matrix, peroxidation of membrane lipid and ATPase activity. HSPC228, EMP1, CDC42, TLE3, SPRY2, p40BBP, HSPC060 and NAB2 or a down-regulation of the expression of HSPAIA, HSPA1B, MAPRE2 and OAS1, TACE / ADA 17, alpha-1-acid glycoprotein, angiopoietin-1, MIF, angiopoietin-2, CD14, beta-defensin 2, M P-2, ECF-L / CHI3L3, M P-7, EGF, MMP-9, EMAP-II, MSP, EN-RAGE, nitric oxide, endothelin- 1, osteoactivin / GPNMB, FPR1, PDGF, FPRL1, Pentraxin 3 / TSG-14, FPRL2, Gas6, PLUNC, GM-CSF, RAGE, S100A10, S100A8, S100A9, HIF-1 alpha, substance P, TFPI, TGF-beta 1, TIMP-1, TIMP-2, TIMP-3, TIMP-4, TLR4, LBP, TREM-1, Leukotriene A4, Hydrolase TSG-6, Lipocalin-1, uPA, M-CSF, and VEGF.

The physiological data for each individual can also be measured and communicated from the instruments of .FS or points of care to the OS. Such data may include without limitation temperature, heart rate / pulse, blood pressure, oximetric signals, weight, water retention, plethysmographic signals, respiratory rate, fat content, water content, blood perfusion, mobility, posture, bioelectrical impedance, electrocardiogram (ECG) or galvanic skin response.

In some embodiments, the assays are used to detect host antibodies against a particular pathogen or marker. A potential problem when measuring such antibodies is the interference that may occur in individuals who have had influenza vaccinations in the past. In such situations, high titers of influenza antibody in the blood can interfere with the analysis. Influenza virus replicates mainly in the lungs and can therefore be detected, for example, in sputum, nasal lavage and saliva. Therefore, a saliva-based sample can also be processed at the point of care for verification. Hemagglutinin antigen (H antigen) on the surface of influenza particles is believed to be instrumental in the. entry of the virus into the target cells. The hemagglutinin can bind red blood cells and under appropriate conditions causes the cells to agglutinate. Thus, red blood cells in the blood can act as concentration agents for the virus. This phenomenon can be exploited in analysis by the virus since red blood cells can be concentrated before a blood sample is analyzed. Further,; red blood cells can be collected (and concentrated) on an appropriate surface in an analysis cartridge, thereby presenting large quantities of virus for analysis and detection.

Two key assessment measures of any insertion test or medical diagnosis are its sensitivity and specificity, which measure how well the test performs to accurately detect all affected individuals without exception and without falsely including individuals who do not tend to target disease ( predicted value).

A true positive result (TP) is where the test is positive and the condition is present. A false positive result (FP) is where the test is positive but the condition is not present. A true negative result (TN) is where the test is negative and the condition is not present. A false negative result (FN) is where the test is negative but the condition is not present. In this context: sensitivity = TP / (TP + FN); specificity = TN / (FP + TN); and predictive value of a positive = TP / (TP + FP).

Sensitivity is a measure of the ability of the test to correctly detect the target disease in an individual that is tested. A test that has low sensitivity produces a high proportion of false negatives, that is, individuals who have the disease but are I falsely identified as being free of that particular disease. The potential danger of a false negative is that the sick individual will remain undiagnosed and and untreated for a period of time, during which the disease may progress to a later stage where, if any, treatments may be less effective. An example of a test that has low sensitivity is; a protein-based blood test for HIV. This type of test exhibits poor sensitivity because it fails to detect the presence of the virus until the disease is well established and the virus has invaded the bloodstream in substantial numbers. In contrast, an example of a test that has high sensitivity is viral load detection using the polymerase chain reaction (PCR). High sensitivity is obtained because this type of test can detect very small amounts of the virus. High sensitivity is particularly important When the consequences of failing a diagnosis are high.

Specificity, on the other hand, is a measure of the ability of the test to accurately identify patients who are free from the disease state. A test that has low specificity produces a high proportion of false positives, that is, individuals who are falsely identified as having the disease. A deficiency of false positives is that they force patients to suffer unnecessary medical treatments with their concurrent risks, emotional and financial efforts and that could have adverse effects on the patient's health. Specificity is important when the cost or risk associated with additional diagnostic procedures or very high additional medical intervention.

In some modalities, the HS performs multiple analyzes to improve the sensitivity and / or specificity of the analysis. For example, the sensitivity and specificity of disease monitoring can be improved. In some modalities, multiple body samples are analyzed for an individual. For example, tests based on saliva and blood (finger prick) can be put into operation simultaneously for people who have been previously vaccinated by influenza. 'Testing multiple samples may increase the likelihood of identifying the infection. In addition, it may be important to control false negatives to maximize containment. In some embodiments, the present invention treats false negatives by including tests for both inflammation markers and infection in each test cartridge. Where the influenza test is negative but these other markers are strongly suggestive of influenza, confirmatory tests can be included for that specific subset of patients. A variety of exemplary marker panels, also referred to as test menus, are disclosed herein for various disease configurations. The skilled artisan will appreciate that the use of multiple analyzes and / or physiological parameters to improve sensitivity and / or specificity is not limited to these exemplary modalities but rather can be an effective technique when monitoring many diseases and disorders.

In some modalities, the HS decentralized detection capability provided by the FS units can: provide the premature identification of people with a confirmed case of influenza, that is, an "index case" and then put in a row all the close contacts than those individuals so identified. Given that such a network of contacts, which contains epidemic spreading, ideally requires rapid deployment, identification and immediate action and in an exposed and / or asymptomatically infected population. The HS provides a system to carry out these operations and prevent the spread of disease.

The Health Shield system can be deployed for the surveillance and containment of an influenza outbreak. The HS can be deployed in a variety of facilities, for example, locally, regionally or nationally. The OS for a given installation can use in silico modeling to simulate various deployment strategies to better contain the influenza or other condition and can be optimized for each installation. In some modalities, the model comprises an epidemiological model that includes a variety of appropriate parameters to model the expected outbreak and / or content. In some modalities, the system uses simulations of. Monte Cario to 'test a spectrum of selection and containment strategies that, in turn, will be analyzed in terms of cost / benefit ratios, etc. For example, the system can project where and how to deploy limited resources, for example, medical personnel, therapeutic treatments and vaccines. The OS model can be pre-loaded with specific information of the population and individual, for the installation to be monitored. These factors include but are not limited to incubation time, connectivity of the susceptible population, manner of infection, virus virulence, proportions of deaths and proportions of hospitalization, incidence of disease, mode of transmission, infection rate, therapeutic intervention results. , vaccine efficacy and resistance to or effectiveness of anti-viral therapy, for example, Tamiflu. Parameters for individuals who are monitors include without limitation age, sex, social contacts (life arrangements, family, partners, etc.), prior history? of illness, general health (for example, other pre-existing conditions), etc. The parameters of the model can be "continuously updated once the system is deployed.

FS instruments are deployed to operate in conjunction with the configured OS. In some modalities, the data of the FS are provided to an OS by means of a portal of programming elements. The remote OS can then perform the desired calculations. In general, FS systems are deployed to selected hot spots. In some modalities, the OS model is used to direct the optimal deployment of FS instruments. Optimal and hot spot locations include, without limitation, areas where people gather, for example, shopping areas, schools and workplaces. Locations where ill people come together are also targeted, including without limitation clinics, pharmacies and hospitals. In some embodiments, FS devices are deployed in homes, as described herein.

Once deployed, the FS systems are used to test the subjects. In some embodiments, this includes tests for disease antigens, e.g., viral coat proteins. The analytes also include host proteins as markers of disease, for example, immune markers including cytokines and inflammatory markers indicating an ongoing infection. In the detection of infectious disease agents and evaluation of the status and prognosis of patients, it may be desirable to be able to measure multiple analytes simultaneously. For example, this increases the probability of detecting disease since any individual analyte may not be found at abnormal levels. Multi-analyte measurements also reduce noise and can make the system more accurate in disease monitoring.

The following table presents an exemplary menu for detection of H1N1 virus, also known as swine influenza: Table 3 In the table, "Ab: Ag" represents the complex formed between an antibody (Ab) and an antigen (Ag). For example, "anti-Hl: Ig H1" represents a complex between the host IgG anti-Hl antibodies and the Hl antigens of influenza hemagglutinin. Since different strains of influenza are monitored, the menu will be adjusted accordingly. For example, a menu to monitor H1N5 virus will include detection of the N5 antigen and anti-N5 antibodies.

The detection of IgM antibodies against IgG or IgA can be used to determine if an individual had a prior exposure to the influenza particles of interest. The IgM antibodies are elaborated rapidly in the days following the infection at the first exposure to an immunogen. When previously exposed individuals find a second infectious agent that has similar or identical antigenic character, IgG and IgA antibodies are produced very quickly. This secondary response is commonly much stronger and more specific than the original IgM response. In primary infections and very severe infections, the active virus is more likely to be present in the blood and to be directly detectable. In secondary infections, where the antibody is present, it will be in general in excess on the antigen and the antigen can be masked to the immunoassay methods. In some embodiments, the complex formed by the antigen and antibody is detected using a sandwich immunoassay in which one reagent is directed to the antigen and the other to IgG. Once a subject produces IgG and IgA antibodies, such antibodies can be found in the blood after the infection has resolved.

As shown in Table 3, the menu may also include one or more cytokines as a marker of immune response and / or inflammation. Cytokines of interest include without limitation IL-? ß, IL-6, IL-8, IL-10 and TNFOI. Cytokines such as these can be produced in large quantities during the premature part of a viral infection. In some cases, the level of these markers will rise and fall rapidly. Valuable information regarding the status of the patient and prognosis can be obtained by making serial measurements of one or more cytokines. For exampleFevers of viral and bacterial origin can be distinguished by measuring changes in cytokine levels. A recent study found that "CRP velocity" (CRPv), defined as the ratio between C-reactive blood protein in admission to an Emergency Room and the number of hours since the onset of fever, can differentiate between acute febrile bacterial disease and non-bacterial febrile disease. Paran et al., C-reactive protein velocity to distinguish bacterial infections from non-bacterial febrile illnesses in the emergency department, Crit Care. 2009; 13 (2): R50. The study also found that blood levels of other acute phase proteins, such as IL-1, IL-6, and TNF-OI, correlate with CRPv.

The levels of detection of influenza markers are shown in Table 4: Table 4: Threshold or action levels for influenza bio-markers The exemplary markers in Tables 3 and .4 correspond to a menu for HlNl detection. The threshold levels for detecting a certain marker are shown in Table 4. When the measurements are made in a time course, the times of increase in a marker, for example, cytokines or C-reactive protein can be detected. Here, a change 10 x is considered an indicator of an event. When time course data for an individual are not available, the times of change can be determined by comparing with a reference threshold. For example, the detected level of a given marker can be compared with the average level of the marker in the healthy population ^ in general. It will be appreciated that different strains of influenza, for example, H5N1, H3N2, etc., can be detected using appropriate analytical methods.

A recommended course of action of OS for influenza when a given marker is detected is shown in Table 5.

Table 5: Suspected swine influenza action matrix As before, the example in Table 5 highlights swine influenza H1N1. It will be appreciated that different strains of influenza, for example, H5N1, H3N2, etc., can. be detected using appropriate analytical methods. In addition, the action will depend on a variety of factors, including but not limited to expected virulence, transmission, treatment cost, etc. For example, a quarantine may be required for a virulent strain but not for a less severe outbreak. The recommended course of action for drug resistance may depend on the drug. In the configuration of influenza, resistance to oseltamivir (Tamiflu®) may be especially important. Oseltamivir is an orally active antiviral drug that acts as a neuraminidase inhibitor. The drug slows the spread of influenza virus (flu) between cells in the body by preventing the new virus from chemically cutting moorings with its host cell. It can be used for both influenza A and influenza B.1! Resistance can be determined by a number of methods, for example, a functional analysis (culture) or identification of a genetic marker. Zanamivir is also used to treat influenza infection.

Specific strains of influenza viruses can be detected using a sandwich analysis format. A number of analysis configurations can be used. Figure 3 illustrates analysis for the H1N1 antigen illustrating sandwich complexes in four different types of analysis. The skilled artisan will understand that a similar arrangement can be used to detect other strains of viruses, for example, H5N1, H2N3, etc. The final reaction products are shown for four analysis configurations for measuring the H1N1 virus (which has several copies of each on the viral particle). The assays involve: 1) adding the sample, eg blood, serum, saliva or nasal wash, to a capture surface having an antibody to one of the viral surface antigens (Hl, NI); 2) add the enzyme-labeled antibody to one of the surface antigens; and 3) washing the surface to remove the viral particles without binding. The different analysis configurations can detect several particles. The a-Hl / a-Nl and -Nl / a-Hl configurations will measure H1N1 viruses, the a-Hl / a-Hl configuration detects any virus that has Hl antigen and the a-Nl / a-Nl configuration detects any virus that has the NI antigen. A cartridge system for detecting the analyzes is described in US patent application 11/746, "535, filed on May 9, 2007 and entitled" REAL-TIME DETECTION OF INFLUENZA VIRUS ".

Sandwich assays can also be used to detect host antibodies to influenza strains, for example, human antibodies to swine influenza H1N1. A first mode of such analysis is shown in Figure 4A. In the figure, the capture phase of analysis has an antibody to the viral antigen attached to a solid phase ii The viral particle (antigen) can be captured by the solid phase and a detection reagent, for example, alkaline phosphatase-labeled antibody to viral antigen, can be used to detect host antibodies. This analysis is configured as an antigen analysis. The antibody is detected by projecting the viral antigen into the sample, for example, body fluid such as blood or plasma and comparing the test response with and without added antigen. Anti-viral antibodies can be measured by adding (projecting) a known fixed amount of virus or viral antigen to the patient's sample. Following the incubation, the projected sample is used in an analysis for the viral antigen. If antibodies are present, the analysis will show reduction in the measured antigen (low projection recovery). The sample dilution or the level of the projected antigen can be titrated to give a quantitative value for the antibody. When the antibody to the viral antigen is present, there is little or no signal generated in the absence of the added antigen. There is a reduced (or zero) response when the antigen is added compared to the response to antigen-negative control samples that were projected with antigen. In other words, the "projection recovery" of antigen is low or zero. The amount of antibody can be deduced from the projection recovery if it is more than zero. The antibody in the sample can also be titrated by using increased antigen projections until an analysis response is obtained. Those of skill in the art will appreciate that the assays can be adapted to detect host antibody to other strains of viruses, e.g., H5N1. The method can also be adapted to detect host antibodies to any appropriate antigen, for example, to other microbial attacks.

Another configuration to detect. host antibodies to viral influenza particles is shown schematically in Figure 4b. This is a direct detection method. In this embodiment, the analysis capture phase has viral antigen attached to a solid phase and uses a detection reagent consisting of alkaline phosphatase-labeled antibody to human immunoglobulin. As described herein, the host antibody ideotype can determine whether the host is naibe to the f6 antigen (igm antibodies are found) or has had prior exposure (igg or iga antibodies are found). By the use of antibodies specific to immunoglobulin species (eg, igm, igg, iga, etc.), the type of antibody can be determined. The analysis involves: 1) incubating the sample with a capture surface to which the virus and / or viral antigen is linked; 2) wash the surface to remove the igg without binding, then 3) incubation with; an enzyme-labeled anti-human immunoglobulin specifies now! be for igg or igm; 4) washing to remove enzyme-labeled antibody without binding and 5) incubation with substrate. Figure 4b shows the status of merit after the fourth stage.

FS systems are used to monitor granites and others for individual monitoring (blood pressure, temperature, weight, etc.) over time. In some modalities, tests are performed on an individual at a set time, for example, one or more analyzes could be performed at least every 1 hour, 2 hours copy data, 2 days, 3 days, copy data, 2 weeks, 3 Copy data, 4 months, 5 months copy data or at least every year. The frequency of tests may vary between individuals and between different diseases. For example, those considered at risk, for example, school children, adults, health care workers and doctors, can be tested more frequently. In some modalities, the OS directs the frequency of analysis. For example, the OS can identify those at risk in more frequent schedule tests. The tests can also be programmed in real time or semi-real time. For example, once an index case is identified, other individuals in social contact with the index case could be tested immediately and more frequently thereafter. In some modalities, the test frequency is increased by a hot spot with increased risk. In some modalities, the frequency of tests is reduced as the risk is reduced, thus saving resources.

As indicated, a variety of field devices can be used by the systems and methods of the invention. The OS can direct an optimal deployment of! 1 FS devices. In some modalities, the types of analyzes are adjusted over time as the nasa changes, for example, to monitor different analytes. In some modalities, the type or types of sample! they are adjusted over time as the threat changes. In addition, viral nucleic acid has been detected? in blood using techniques of per for example, per in time i; real. In some embodiments, cartridges, multi-sample type as defined herein are used. These cartridges allow the processing and analysis of samples of a limited number of analytes in more than one type of sample, for example, using one or more of blood, concentrated red blood cells, sputum, saliva, nasal lavage or other body fluid. In some embodiments, miilti-analyte cartridges as described herein are used. These cartridges can perform analyzes of many analytes in a single sample type. Both types of cartridges can be used in a given installation as considered optimal in a given installation.

The deployed FS systems are used to test the types of samples selected using the selected analyzes and the results are reported back to the OS system as described herein. Influenza infection was possible in the evaluation of individuals, it is advantageous to make a series of measurements with respect to time. Based on premature measurements, the established ideal analyte can be changed to optimize the information gathered by the analysis system. The use of such longitudinal measurements allows the calculation of trends in analyte levels that indicate trends in disease processes. In some embodiments, the longitudinal measurements of the invention take into account the dynamic data of particular individuals together with population information gathered in previous epidemics. In some modalities, the models also adjust cut data from subjects exposed to a current epidemic.

The OS monitors incoming data regarding infection incidence and provides the determination and containment recommendations when an infection is found. When an infection is observed, the appropriate parties are notified, for example, individual, social contacts of the same, health care workers and government officials. In some modalities; the body of action recommended by the OS is used to contain the spreading of the virus. In some modalities, the course of action includes providing therapeutic treatment to an infected individual. In some modalities, prophylactic treatment is administered to those in contact with the infected individual. This could include vaccination. In some modalities, depending on the severity of the brpte, individuals may be quarantined. Those who have contact with the infected individual can be quarantined as well.

The FS and OS continue to monitor from start to finish and continuously update the OS database with incoming information. In some modalities, the OS adjusts the recommended course of action in response to measurements, from the real world. In this way, the health shield of the present intention provides a dynamic response to the detected outbreak. Once an outbreak has been contained the FS components of the system can be relocated to alternative hot spots, etc. 6. Monitoring of infectious disease.

It will be appreciated that the systems of the invention as defined above can be employed to monitor the incidence of a number of infectious diseases, in addition to influenza. For example, hs can be deployed to monitor and prevent the spread of infectious diseases in areas where resources are limited, for example rural or remote areas or developing countries. In some modalities, hs is used to monitor acquired immune deficiency syndrome (AIDS), tuberculosis (tb) and / or malaria. AIDS is a disease of the human immune system caused by the human immunodeficiency virus (HIV). HIV is remitted through direct contact of a mucous membrane or bloodstream in a body fluid containing HIV, such as blood, semen, vaginal fluid, pre-seminal fluid and breast milk. The disease is also for AIDS due to sharing syringes that are infected or used to inject illicit drugs. AIDS progressively reduces the effectiveness of the immune system and leaves individuals susceptible to opportunistic infections and tumors. This weakening of the immune system exacerbates the risks of TB and malaria. Tuberculosis is an infectious, common and often fatal disease caused by lymphobacteria, for example microbacterium tuberculosis. Tuberculosis resides mainly in the lungs and is spread by means; of air, when infected individuals cough, sneeze or spit. Malaria is an infectious disease transported by vector caused by protozoan parasites and is spread by the picket of an infectious female anopheles mosquito. AIDS, TD and malaria each kill more than 1 million people a year. The majority in developing countries. Treatments are available for these infectious agents, but the cost of treatment varies widely. Td and malaria treatments are relatively inexpensive but AIDS treatments can be expensive. Drug resistance may be a concern for all of these pathogens.

In some modalities, the HS system is deployed to monitor and limit the spread of infectious diseases including AIDS, TD and malaria. In some modalities, this configuration of the health shield is deployed in developing countries. The general infrastructure may be similar to that described above for influenza. The data entered into the model may include pharmacogenetic data and pharmacodynamic data (PK / PD) for several drugs and combination of drugs administered for the diseases. Analysis for drug resistance can also be included in FS systems. The system can also gather information about individuals' compliance with drug therapy. Through this, the system can estimate the optimal treatment regimen for each individual. Given the profile of the individual, a person can be treated with a drug regimen indicated to cure the progression of the disease. Another individual can be assigned a treatment which is optimal for quick cure, but will have a higher compliance rate (eg less treatment, 'for example less pills a day) and finally get better long-term results for that individual .

FS systems can be located in hot spots under development. Hot spots may include, for example, areas with a higher number of infectious mosquitoes or areas where individuals have less ability to protect themselves from mosquito bites. In some modalities, central test zones can be built inside the hot spots. In some modalities, individuals having access to energy may have blood samples taken and donated or analyzed in a central laboratory facility that has the necessary resources. These labs can be located in or near hot spots. In some modalities, the central laboratories are contained in mobile units that can be moved to the location of the individuals.

The HS systems of the invention can be configured to provide strategies and recommendations for controlling the growth of the disease. Individuals and organizations in a hot spot or monitored area can be educated about the disease eg cause, treatments and methods to avoid recreation. In some modalities, OS models' suggest active protective measures. For example, if the system identifies an emerging hot spot for tb, extra mosquito networks, accusations for insects, insecticides or anti-insecticides can be deployed to that area. Vaccinations or prophylactic treatments can also be administered. In some modalities, the model predicts areas where the infection is most likely to spread, thus allowing premature or preventive vaccination in those areas to prevent the disease. Individuals or groups of infected individuals can be placed for supervision or quarantine. In some modalities, individuals are quarantined within their home, a hospital or other care facility. Additionally, the contacts of an infected individual, for example friends, family or colleagues may be placed in quarantine? Placed under close monitoring or surveillance. In some modalities, the hs system identifies carriers, that is, individuals who carry the disease but are not symptomatic. For example, approximately 80% of the population in Africa tests positive for tuberculosis. In some modalities, stages are undertaken to reduce recreation by carriers. For example, carriers can be treated, educated about methods to reduce spreading, for example, avoid exchange of body fluids or hygienic methods or quarantine as appropriate. The OS system can provide estimated values of the global benefits and cost / benefit analysis of various actions to be taken.

The analysis of the efs systems can be designed to measure analytes specific to the disease or disease that is monitored. Non-limiting examples of analytes when monitoring AIDS, td, and malaria include HIV virus, HIV viral arm, IgM antibody to HIV, IgG antibody to HIV, CD4, and Td8 and / or drug treatment. Non-limiting examples of analytes measured when td is monitored include td antigens, anti-d antibodies, nicobacterium and gamma interferon antibodies that can be elevated after infection. Non-limiting examples of analytes measured when malaria is monitored include malarial antigens and anti-malaria antibodies. Several actions that can be undertaken when detecting AIDS analytes include actions on scales of Table 6.

Table 6. Matrix of action analytes for AIDS.

Analyte or analytical indication Viral virus Low p-cell auxiliary content Low ratio of CD4 / CD8 Igm antibodies to viruses IgG antibodies to viruses Protective antibody Antibody to tnb Antibody to herpes virus Viral resistance to drugs Viral resistance to drug combinations Non-optimal drug level Increase in viral RNA level Decrease in gd4 Decrease in gd4 / cd8 Interpretation Current infection Recent infection Established infection Subject for investigation Risk of blindness Severe herpes risk Virus mutation Viral outbreak Action Try Start treatment Tatar Monitor / treat Change of drug Change combination Adjust Treat aggressively Community action Advise contacts Advise contacts Track contacts None none Advise contacts Copy data In some embodiments, the systems of the invention are used to monitor chronic incurable infectious diseases. Such diseases are spread by contact with infected blood and other bodily fluids. AIDS is currently incurable but individuals with HIV can sometimes live decades through the use of antiviral treatments. Transmission can be reduced by more than 80% through the appropriate use of condoms, restriction of sexual partners and abstinence. Hepatitis b and c are chronic liver diseases caused by infection with hepatitis B and C viruses, respectively. The health shield of the present invention can be used to monitor the health status of those with hepatitis, similar to another infectious disease as described herein. For example, methods of containment in hot spots can be implemented, for example education and distribution of condoms can be used to avoid contact of hepatitis c by sexual contact.

At the individual level, appropriate education and therapy or interventions may be assigned to infected individuals if the condition worsens. For example, liver baths in the late stages of hepatitis can be made worse by alcohol abuse. Infected individuals can be educated about such adverse effects of alcohol. Non-limiting examples of analytes measured when hepatitis is monitored include hepatitis B viral antigens, hepatitis C viral antigens, hepatitis B viral DNA, hepatitis C viral DNA, anti-hepatitis B surface antigen antibodies, anti-surface antigen antibodies -hepatitis c, anti-hepatitis b core protein antibodies, anti-hepatitis c protein core antigen antibodies c. Non-limiting examples of analytes measured when liver function is monitored include aspartate transaminase (ast) or analin transaminase (ant). The ratio of ans / alt is sometimes useful in differentiating certain causes of liver damage when the liver enzymes are elevated. For example, a ratio greater than 2.0 is more likely to be associated with alcohol hepatitis while a ratio less than 1.0 is more likely to be associated with viral hepatitis.

Those of skill in the art will appreciate that the Health shielding system can be configured and adapted for the monitoring and containment of any number of infectious agents using similar procedures as described herein. The present invention includes the monitoring of the following non-limiting infectious agents and analytes thereof: adenovirus, Bordella, chlamydia pneumoia, Chlamydia trachomatis, cholera toxin, cholera beta toxin, Campylobacter jejuni, cytomegalovirus, diphtheria toxin, Epstein NA -Barr, Epstein-Barr EA, Epstein-Barr VCA, Helicobacter pylori, hepatitis B virus (HBB) center, hepatitis B virus envelope (HBB), Hepatitis B virus (HBB) surface area (Ay) , core of hepatitis C virus (HCB), hepatitis C virus (HCB) NS3, hepatitis C virus (HCB) NS4, hepatitis C virus (HCB) NS5, hepatitis A, hepatitis D, hepatitis E virus (HEB) ) orf2 3 KD, hepatitis E virus (HEB) orf2 6 KD, hepatitis E virus (HEB) 0RF3 3KD, human immunodeficiency virus (HIV) -1 p24, human immunodeficiency virus (HIV) -l gp41, I human immunodeficiency virus (HIV) -l gpl20, human papilloma virus (HPV), herpes simplex virus HSV-1/2, herpes simplex virus HSV-1 gD, herpes simplex virus HSV-2 gG, human human T cell leukemia (HTLV) -1 / 2, Influenza A, Influenza A H3N2, influenza B, Leishmania donovani, mumps, Lyme disease,. pneumoniae, tuberculosis, parainfluenza 1, parainfluenza 2, parainfluenza 3, poliovirus, respiratory syncytial virus (RSV), rubella, rubella, streptolysin O, toxin. of tetanus ,. T. pallidum 15 kd, T. pallidum p47, T. cruz, Toxoplasma, and varicella zoster. 7. Monitoring of Chronic Disease and Efficacy of treatments In addition to monitoring infectious diseases, the Health shield makes it possible to understand the individual's disease trajectory and response to therapy. Given both the inherent genetic variance embedded in the human species and variability of an individual's environment, the ? ability to monitor and track the most informative pathophysiological factors in a disease process allows to determine if a therapy is effective. Such monitoring can help ensure that health care dollars are spent on treatments and drugs that work. With traditional laboratory systems, up to 50% of individuals fail to comply with prescriptions for laboratory tests and as many as 60% of therapeutic prescriptions do not have the proposed effects. The hs provides greater compliance via home deployment and greater effectiveness of the drugs by monitoring in real time; the effectiveness Because the HS of care, helps to facilitate the Lab tests.

In some embodiments, the integrated technologies of the invention are used to manage chronic diseases such as congestive heart failure, i; Such monitoring can help improve the quality of life and lead to costly hospitalizations through preventive action. For diabetic individuals, the systems can provide automated counseling that helps to coordinate and manage lifestyle change and reverses the progression of the disease and prevents (and predicts) complications. By improving the results and allowing premature interventions ,,; You can get savings from health care i significant. In some modalities, the same systems can be used to monitor interactions among drugs for chronic disease patients who take multiple therapies. This ability not only prevents i, adverse drug reactions and reduces costs! of associated complications, but also potentially lifesaving drugs can be used more widely in populations with chronic disease.

Diabetes melitus (diabetes) is a condition in which the body either fails to produce properly or respond to insulin, a hormone produced in the pancreas that allows cells to absorb glucose in order to convert it into energy. In diabetes, the body either fails to respond appropriately to insulin, does not make enough insulin, or both. This causes glucose to accumulate in the blood, leading to Acute complications include Diabetic or non-ketotic hyperosmolar coma can occur if the disease is not monitored properly. Complications a Long-term serious diseases include cardiovascular disease, chronic renal failure, retinal damage and blindness, watts i types of nerve damage, and microvascular damage, which can cause erectile dysfunction and poor healing; of wounds. Scarce wound healing, particularly of the feet, can lead to gangrene, and possibly amputation. In type 1 diabetes, or juvenile diabetes, the body fails to produce insulin. Currently 1 almost all people with type 1 diabetes should take insulin injections. Type 2 diabetes, also known as adult onset diabetes or late-onset diabetes, results from insulin resistance, a condition in which cells fail to use insulin properly, sometimes combined with relative insulin deficiency. 'Approximately 90% of Americans who; They are diagnosed with diabetes have type 2 diabetes. Many people destined to develop type 2 diabetes spend many years in a pre-diabetes state, a condition that occurs when the person's blood glucose levels are higher. that normal but not high enough for a type 2 diabetes diagnosis. With respect to 2009 there are 57 million Americans who have pre-diabetes.

Pre-diabetes has been called "the largest health care epidemic in the United States." Handelsman, Yehuda, MD. A diagnostic doctor: Prediabetes. Power of prevention, Vol. 1, Number 2, 2009. Diets high in sugar and high in fat are causing premature onset of obesity and diabetes, especially in rich countries. Young people consume a diet high in sugar and fat and become obese, which can in turn lead to serious illnesses and disorders, including but not limited to prediabetes, diabetes, heart disease. In many environments, easy access to carbonated beverages that contain high levels of sugar and fast, high-fat foods promotes this process.

The HS system of the invention can be used to assist in the response to the spread of diabetes. In some embodiments, the system is used to identify individuals at high risk. In some modalities, the system can identify locations, geographical locations, communities, school systems or schools, where the risk of disease progression is higher. In a non-limiting example, consider that the HS is deployed in a school. The FS system would be deployed to the school in a manner similar to that described above for infectious diseases. In some modalities, school employees, for example, the school nurse, could administer analyzes to all students or a subset of students, for example, at-risk students. The tests may be carried out at regular intervals, for example, at least once a school year, at least once a semester, at least once a quarter, at least once a month, at least every three weeks, at least every two weeks, or at least weekly. In some modalities, subsets of students could be tested at different intervals. For example, the entire body of students could be tested at a first frequency, and a subset of the body of students, for example, those identified as at risk for several factors, for example, obesity or the result of previous tests, could be monitored at a second frequency. In a non-limiting example, the first frequency could be at least once a school year and the second frequency could be at least once a semester, at least once a quarter, or at least once a month. Any similar scheme, where those at risk 'are tested most frequently can be used.

FS systems deployed in schools can be used to monitor a variety of analytes • that are indicators of risk or disease, for example, hormone levels and glucose levels. In some embodiments, such analytes are measured in blood. Non-limiting examples of appropriate analytes that can be measured by FS systems are glucose, hemoglobin Ale, insulin, glucagon, glucagon-like peptide-1 (GLP-1), insulin precursor peptide-C, leptin, HDL adiponectin, cholesterol, HDL cholesterol, LDL cholesterol and triglycerides. Other physiological data, such as body mass, can also be introduced to the system so that the S component of the HS calculates individual and group risks. The system can also monitor drug therapy, introduce a regimen to the health profile of the individual, or directly detect levels of the drug with FS. In some modalities, the system monitors the progress of any, or all of these, variables over time.

When the HS identifies an individual, for example, a student, or a population, eg, a body of students, who have or are at risk of developing prediabetes or diabetes, the system may recommend a course of action. In the case of a population, the system can issue a warning and / or recommend action if the population or risk incidence increases above a threshold level. In some modalities, the course of action includes advising individuals, health caregivers or other individuals that can influence the lifestyle of the individual to mitigate the disease or risk of the same. For example, parents. or school officials can be notified. The system may also recommend therapies or interventions, including exercise, weight loss, altered food habits, etc., for a population, a recommendation could include population control measures, including, without limitation, the removal of sugary soft drinks , from school facilities, healthier cafeteria menus, and improved physical education.

The susceptibility to type II diabetes is not only due to poor lifestyle choices, but is affected by other factors, for example, genetic factors. In the United States of America, such variation, for example in the native American population and those with significant indigenous ancestry, such as the Hispanic population, are potentially at high risk. Environmental factors are also | potential factors. The OS model can be extended to take into account additional factors, including, without limitation, genetic factors and environmental factors. For example, the model may be configured to include adaptive sampling based on risk measurements without analysis. Such risk measures include, but are not limited to, body weight, medical history, blood pressure, family history, activity level, genetic variability, and alcohol use. The model can also be configured to adaptive sampling based on FS analysis data in conjunction with geographic, family, demographic, employment, health care provider, and other data. Similarly, the system can model adaptive therapeutic treatment based on the results for the individual and for a population that the analysis system determines are similar for the variables that best indicate the risk. 'The system can also incorporate visualization that helps the doctor explain and clarify to the user their risk factors, and appropriate actions to mitigate the risk, for example, therapeutic and / or prophylactic treatments and / or interventions, weight loss, changes in diet, exercise and other lifestyle changes. Such a visualization could include, for example, a decision tree or heat map. In some modalities, the visualization shows the cumulative risk of additive factors. An exemplary use of a decision tree for diabetes is presented in Example 4. Each of these procedures can be applied to the model for diabetes and other chronic or infectious diseases.

In another modality, HS monitoring and real-time point-of-care capabilities can be used to improve the efficiency of clinical trials. The time-saving impacts of the Health shield have been quantified next to conventional and analytical data tests by pharmaceutical companies. Modeling studies show that HS can reduce the clinical testing process by potentially a number of years and save $ 1 billion per program. In addition, the data generated can provide better success and results for the drugs monitored when defining patient populations and identify possible adverse events in a predictive manner.

In a separate embodiment, a method is provided for monitoring more than one pharmacological parameter useful for determining the efficacy and / or toxicity of a therapeutic agent. For example, a therapeutic agent can include any substance that has utility and / or therapeutic potential. Such substances include, but are not limited to, biological or chemical compounds, such as simple or complex organic or inorganic molecules, peptides, proteins (e.g., antibodies) or polynucleotides (e.g., anti-sense). A vast array of compounds can be synthesized, for example polymers, such as polypeptides and polynucleotides, and synthetic organic compounds based on several different structures, and these can also be included as therapeutic agents. In addition, several natural sources can provide compounds for therapeutic use, such as plant or animal extracts, and the like. It should be understood that although it is not always explicitly stated that the agent is used alone or in combination with another agent, which has the same or different biological activity as the agents identified by the selection of the invention. The agents and methods are also intended to be combined with other therapies. For example, small molecule drugs are often measured by mass spectrometry that can be inaccurate.), ELISA (antibody-based) assays can be much more accurate and accurate.

Physiological parameters according to the present invention include, without limitation, SUCH parameters as temperature, heart rate / pulse, blood pressure and respiratory rate. Pharmacodynamic parameters include biomarker concentrations, such as proteins, nucleic acids, cells, and cell markers. Biomarkers could be indicators of disease or could be the result of the action of a drug. Parameters Pharmacokinetics (PK) according to the present invention include, without limitation, drug concentration and drug metabolite concentration. The identification and quantification of the Pe parameters in real time of a sample volume is extremely desirable for the safety and appropriate efficacy of drugs. If the drug and metabolite concentrations are outside a desired range and / or unexpected metabolites are generated due to an unexpected reaction to the drug, immediate action may be necessary to ensure patient safety. Similarly, if any of the pharmacodynamic (PD) parameters falls outside the desired range during a treatment regimen, immediate action may have to be taken as well.

To be able to monitor the rate of change of an analyte concentration or PD or PK parameters over a period of time in a single subject, or to perform trend analysis on the concentration, or PD or PK parameters, if they are concentrations of drugs or their metabolites, can help prevent potentially dangerous situations. For example, if glucose were the analyte of interest, the concentration of glucose in a sample at a given time, also as the rate of change of the glucose concentration in a given period could be highly useful for predicting and avoiding, for example, hypo glycemic events. Such trend analyzes have broad beneficial implications in the drug dosing regimen. When multiple drugs and their metabolites are concerned, the ability to point a trend and take proactive measures is often desirable.

A variety of other diseases and conditions can be monitored using the system, HS and methods described herein. For example, the system can be used to monitor and control the spread of a microorganism, virus or Chlamydiaceae. Exemplary microorganisms include but are not limited to bacteria, viruses, fungi and protozoa. Analytes that can be detected by the present method also include blood-borne pathogens selected from the non-limiting group, consisting of: Staphylococcus epidermis, Escherichia coli, Methicillin-resistant Staphylococcus aureus (MRSA), Staphylococcus aureus, Staphylococcus hominis, Enterococcus faecalis, Pseudomonas aeruginosa, Staphylococcus capitis, warneri aureus, Klebsiella pneumoniae, Haemophilus influenzae, Staphylococcus simulans, Streptococcus pneumoniae and Candida albicans.

Other microorganisms that can be detected by the present method also encompass a variety of sexually transmitted diseases selected from the following: gonorrhea (Neisseria gorrhoeae), syphilis (Treponeena pallidum), chlamydia (Clamyda trachomitis), non-gonococcal urethritis (Ureaplasm urealyticum) , yeast infection (Candida albicans), canker (Haemophilus ducreyi), trichomoniasis (Trichomonas vaginalis), genital herpes (HSV type I and II), HIV I, II HIV and hepatitis A, B, C, G, also as hepatitis triggered by TT. ¡ Additional microorganisms that can be detected by the methods present encompass a variety of respiratory pathogens including but not limited to Psidomonas aeruginosa, methicillin-resistant Staphylococcus aureus (MSRA), Klebsiella pneumoniae, Haemophilus influenzae, Staphylococcus aureus, Stenotrophomonas maltophilia, Haemophilus parainfluenzae, Escherichia coli, Enterococcus faecalis, Serratia marcescens, Haemophilus parahaemolyticus, Enterococcus cloacae, Candida albicans, Moraxiella catarrhalis, Streptococcus pneumoniae, Citrobacter freundii, Enterococcus faecium, oxytoca Klebsella, fluorscens Pseudomonas, Neisseria meningitidis, Streptococcus pyogehes, Pneumocystis carinii, Klebsella pneumoniae Legionella pneumophila, Mycoplasma pneumoniae, and Mycobacte'rium i tuberculosis.

Any number of biomarkers can be detected in a deployed Health shield. Listed below are exemplary labels according to the present invention: theophylline, CRP, CK-B, PSA, myoglobin, CA125, progesterone, TxB2, 6-keto-PGF-1-alpha and theophylline, estradiol, luteinizing hormone, triglycerides , tryptase, low density lipoprotein cholesterol, high density lipoprotein cholesterol, cholesterol, IGFR.

Exemplary liver markers include, without limitation, LDH, (LD5), (ALT), arginase 1 (liver type), alpha-fetoprotein (AFP), alkaline phosphatase, alanine aminotransferase, lactate, dehydrogenase and bilirubin.

Exemplary kidney markers include, without limitation TNF-a receptor, cystatin C, urinary prostaglandin D type Lipocalin, syntax (LPGDS), hepatocyte growth factor receptor, polycystin 2, polycystin 1, Fibrocystin, Uromodulin, alanine, aminopeptidase, N-acetyl-BD-glucosaminidase, albumin, and retinol binding proteins (RBP).

Exemplary heart markers include, without limitation troponin I (TnI), troponin T (TnT), CK, CK-MB, myoglobin, fatty acid binding protein (FABP), CRP, D-dimer, S-100 protein, BNP , NT- proBNP,. PAPP-A, myeloperoxidase (MPO), isoenzyme BB glycogen phosphorylase (GPBB), thrombin-activatable fibrinolysis inhibitor (TAFI), fibrinogen, ischemia-modified albumin (IMA), cardiotrophin-1, and MLC-I (light chain I of myosin).

Exemplary pancreatic markers include, without limitation, amylase, pancreatitis-associated protein (PAP-1), and Regeneratein (REG) proteins.

Exemplary muscle tissue markers include, without limitation, myostatin.

Exemplary blood markers include, without limitation, Erythopoeitine (OEP).

Exemplary bone markers include without limitation, cross-linked N-telopeptide of type I bone collagen (NTx) carboxyterminal cross-linked telopeptide of bone collagen, lysyl-pyridonoline (deoxypyridonoline), pyridonoline, tartrate-resistant acid phosphatase, procollagen propeptide type IC, Procollagen type IN procollagen, osteocalcin (gla-protein bone), alkaline phosphatase, cathepsin K, COMP (Oligimeric cartilage matrix protein), Osteocrine, osteoprotegerin (OPG), RANKL, sRANK, TRAP 5 (TRACP 5), Factor 1 specific for osteoblasts (OSF-1, Pleiotrophin), soluble cell adhesion molecules of, sTfR, sCD4, sCD8, sCD44, and specific factor 2 of osteoblasts (OSF-2, periostin).

In some embodiments, the markers according to the present invention are disease specific, exemplary cancer markers include, without limitation! PSA (total prostatic specific antigen), creatinine, prostatic acid phosphatase, PSA complexes, prostate-specific gene-1, CA 12-5, carcinoembryonic antigen (CEA), alpha fetoprotein (AFP), hCG (human chorionic gonadotropin) , inhibin, ovarian CAA C1824, CA 27.29, CA 15-3, chest CAA C1924, HER-2, pancreatic, CA 19-9, pancreatic CAA, specific neuron enolase, angiostatin DcR3 (soluble receptor 3), endostatin, Ep-CAM (MK-1), light immunoglobulin Kappa chain, light lambda free immunoglobulin chain, Herstatin, chromogranin A, adrenomedullin, integrin, epidermal growth factor receptor, receptor epidermal growth factor tyrosine kinase, peptide 20N-terminal Pro-adrenomedullin, vascular endothelial growth factor, vascular endothelial growth factor receptor, stem cell factor receptor, c-kit / KDR, KDR, and Midkina.

Exemplary infectious disease conditions include, without limitation: viremia, bacteremia, sepsis, and markers: PMN elastase, PMN elastase / al-PI complex, surfactant protein D (SP-D), HBVc antigen, HBV antigen, Anti-HBVc, anti-HIV, cellular antigen T-suppressor, proportion of antigen T cells, antigen T cellular auxiliary, anti-HCV, pyrogens, antigen p24, muramil-dipeptide.

Exemplary diabetes markers include, without limitation C peptide, hemoglobin Ale, glycated albumin advanced glycosylation end products (AGE), 1,5-anhydroglucitol gastric inhibitory polypeptide, glucose, hemoglobin, ANGPTL3 and 4.

Exemplary inflammation markers include, without limitation, TNF-alpha, IL-6, IL-1 beta, rheumatoid factor (RF), antinuclear antibody (ANA), acute phase markers including C-reactive protein (CRP), Clara cells (uteroglobin).

Exemplary allergy markers include, without limitation, total IgE and specific IgE.

Exemplary autism markers include, without limitation ceruloplasmin, Metalothionein, zinc, copper, B6, B12, glutathione, alkaline phosphatase, and apo-alkaline phosphatase activation.

Exemplary coagulation alteration markers include, without limitation, b-thromboglobulin, platelet factor 4, von Willebrand factor.

In some embodiments a marker can be therapy specific. COX Inhibitors include, without limitation, TxB2 (Cox-1), 6-keto-PGF-l-alpha (Cox 2), 11-dehydro-TxB-la (Cox-1).

Other markers of the present invention include, without limitation, leptin, leptin receptor, and procalcitonin, brain S100 protein, substance P, 8-iso-PGF-2a.

Exemplary geriatric markers include, without limitation, neuron-specific enolase, GFAP and S100B.

Exemplary markers of nutritional status include, without limitation prealbumin, albumin, retinol binding protein (RBP), transrhiprin, acylation stimulating protein (ASP), adiponectin, related Agouti protein (AGRP), angiopoietin-like protein 4 (ANGPTL4, FIAF), C peptide, AFABP (adipocyte fatty acid binding protein, FABP4), protein acylation stimulation (ASP), EFABP (epidermal fatty acid binding protein, FAB'P5), glicentin, glucagon, peptide-1 similar to glucagon, glucagon-like peptide-2, ghrelin, insulin-, leptin-receptor-leptin,, PYY, RELMs, would resist, AMD and sTfR (soluble transferrin receptor).

Exemplary markers of lipid metabolism include, without limitation Apo-lipoproteins (several), Apo-Al, Apo-B, Apo-C-CII, Apo-D, Apo-E.

Exemplary coagulation status markers include, without limitation Factor I: fibrinogen, Factor II: prothrombin, Factor III: tissue factor, factor IV: calcium, factor V: proacelerin, Factor VI, Factor VII: proconvertin, Factor VIII :, factor Anti-hemolytic, Factor IX: christmas factor, X factor: Stuart-Prower factor, factor XI: background of plasma thromboplastin, factor XII: Hageman factor, factor XIII: fibrin stabilizing factor, Precalicreiná, high-weight kininogenin molecular, protein C, protein S, dimer D, tissue plasminogen activator, plasminogen, a2-antiplasmin, plasminogen activator inhibitor 1 (PAI1).

Exemplary monoclonal antibodies include those for EGFR, ErbB2, and IGF1R.

Exemplary tyrosine kinase inhibitors include, without limitation Abl, kit, PDGFR, Src, ErbB2, ErbB 4, EGFR, EphB, VEGFR1 4, PDGFRB, FLT3, FGFR, PKC, Met, Tie2 :, Royal Air Force, and TrkA .

Exemplary serine / Treolin kinase inhibitors include, without limitation AKT, Aurora A / B / B, CDK, CDK (PAN), CDK1-2, VEGFR2, PDGFRB, CDK4 / 6, MEK1-2, mTOR, and PKC-beta.

GPCR targets include, without limitation, histamine receptors for serotonin receptors, angiotensin receptors, adrenoreceptors, muscarinic acetylcholine receptors, GnRH receptors, dopamine receptors, prglandin receptors, and ADP receptors.

Because the HS comprises a series of integrated technologies that can be quickly adapted for further analysis, the system offers a package of ready-made technology different from other systems usually available. For example, systems that focus on a specific technology / application will have great difficulty in improving outcomes and reducing health care expenses through all diseases. 8. Field system cartridges systems.

(A) field system devices.

Cartridge devices made for use with the invention "Point-of-Care-fluidics FS SYSTEMS are described in US Patent Application No. 11/389, 409, filed March 24, 2006 and entitled AND THEIR APPLICATIONS, "US patent application No. 11/746, 535, filed May 9, 2007 and entitled" Real-time detection of Influenza virus "1, and US patent application No. 12/244, 723, filed on 02 October 2008 and entitled "Modular ATTENTION POINT devices, systems, AND APPLICATIONS." Additional details are provided herein.

In one embodiment, an FS device for use with the invention comprises a device for the automated detection of an analyte in a body fluid sample comprising an array of units. of addressable analysis configured to put into operation a chemical reaction that produces a detectable signal indicating the presence or absence of the analyte signal. In some embodiments, the device further comprises an array of addressable reagent units, each of which is addressed to correspond to one or more addressable analysis units in the device, in such a manner; that the individual reagent units can be calibrated with reference to the corresponding analysis unit (s) before the analyzes are assembled in the device. In some embodiments, at least one of the analysis units and at least one of the reagent units are movable together within the device, such that the reagents for putting the chemical reaction into operation are automatically brought into contact with the body fluid sample in the analysis unit. The arrangement of analysis units or reagent units can be addressed according to the chemical reaction to be put into operation by the configured analysis unit.

In one embodiment, the device is self-contained and comprises all reagents, in liquid phase and in solid phase, required to perform a plurality of analyzes in parallel. Where desired, the device is configured to perform at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 30, 40, 50 ', 100, 200, 500, 1000 or more analysis One or more control analyzes can also be incorporated into a device to be carried out in parallel, if desired.

The analyzes can be quantitative immunoassays and can be carried out in a short period of time. Another type of analysis can be performed with a device of the invention, including but not limited to, measurements of nucleic acid sequences and measurements of metabolites, such as cholesterol and enzymes such as alanine aminotransferase. In some embodiments, the analysis is accomplished in no more than one hour, preferably less than 30, 15, 10, or 5 minutes. In other modalities, the analysis is carried out in less than 5 minutes. The duration of the analysis detection can be adjusted according to the type of analysis that will be carried out with a device of the invention. For example, if a higher sensitivity is needed, an analysis can be incubated for more than one hour or up to more than one day. In some examples, analyzes, which require a long duration may be more practical in other POC applications, such as home use, than in an insolation of clinical POC.

Any body fluids suspected of containing an analyte of interest can be used in conjunction with the system or devices of the invention. body fluids Commonly used include but are not limited to blood, serum, saliva, urine, gastric and digestive fluid, tears, feces, semen, vaginal fluid, interstitial fluids derived from tumorous tissue and cerebrospinal fluid.

A body fluid can be extracted from a patient and provided to the device in a variety of ways, including but not limited to, lancet, injection, or picketing. As used herein, the terms subject and patient are used interchangeably herein, and refer to a vertebrate, preferably a mammal, more preferably a human. Mammals include, but are not limited to, murines, apes, humans, farm animals, sport animals, and pets. In one embodiment, a lancet pierces the skin and a sample is collected using, for example, gravity, capillary action, aspiration, or vacuum force. The lancet may be part of the device, or part of a system or an autonomous component. Where needed, the lancet can be activated by a variety of mechanical, electrical, electromechanical activation mechanisms, or any other known activation mechanism or any combination of such methods. In another modality, where no active mechanism is required, a patient can simply provide a bodily fluid to the device, such as, for example, a saliva sample. The collected fluid can be placed in the sample collection unit inside the device. In still another embodiment, the device comprises at least one micro needle that pierces the skin.

The volume of body fluid to be used with the device is generally less than about 500 microliters, commonly between about 1 to 100 microliters. Where desired, a sample of 1 to 50 microliters, 1 to 40 microliters, 1 to 30 microliters, 1 to 10 microliters or even 1 to 3 microliters may be used to detect an analyte using the device.

In one embodiment, the volume of body fluid used to detect an analyte using the present devices and systems is a drop of fluid. For example, a drop of blood from a pierced finger can provide a sample of body fluid that can be analyzed with a device, system or method described in the present.

A body fluid sample can be collected from a subject and administered a device of the invention as described hereinafter.

In one embodiment, the arrangement of the analysis and reagent units are configured to make a set of mixing and matching components. The analysis units may comprise at least one capture surface capable of reacting with an analyte of the body fluid sample. The analysis unit can be a tubular tip with a capture surface inside the tip. Examples of tips of the invention are described herein. A reagent unit commonly stores liquid or solid reagents needed to perform an assay that detects a given analyte. Each unit of individual reactive analysis can be configured for analysis function independently. To assemble a device, the units can be assembled in a manner just in time for use in integrated cartridges.

Separate components, both in liquid phase and in solid phase, can be elaborated and then tested in terms of performance and stored. In one embodiment, the assembly of the device is performed in an over-demand manner at a manufacturing location. The device can be modular and include components such as a housing or box that is generic for all analyzes, analysis units, such as tips, and reagent units, such as a variety of frangible or operable containers. by instruments that encapsulate liquid reagents. In some embodiments, the device is assembled and then tested to define and / or verify the calibration (the ratio of the system response to any analyte levels). Analysis devices can be assembled from a library of pre-manufactured and calibrated elements on demand. In some embodiments, fluid routes within a device can be simple and avoid any chance of catching bubbles and provide an efficient way to wash excess labeled reagents in assays with excess reagents such as ELISA.

A housing for an FS device of the invention can be made of polystyrene or other moldable or machinable plastic and can have defined sites for analysis units and reagent units. In one embodiment, the housing has means for immunoabsorption pits or analysis units to remove excess liquid. The means for immunoabsorption can be a porous membrane, such as cellulose acetate, or a piece of fibrous material such as filter paper.

In some embodiments, at least one of the components of the device may be constructed of polymeric materials. Non-limiting examples of polymeric materials include polystyrene, polycarbonate, polypropylene, polydimethylsiloxanes (PDMS), polyurethane, polyvinyl chloride (PVC), polysulfone, polymethylmethacrylate (PMMA), acrylonitrile-butadiene-styrene (ABS), and glass.

The device or the subcomponents of the device can be manufactured by a variety of methods including, without limitation, stamping, injection molding, embossing, casting, blow molding, machining, welding, ultrasonic welding, and thermal bonding. In one embodiment, a device is manufactured by injection molding, thermal bonding, and ultrasonic welding. The subcomponents of the device can be fixed to each other by thermal bonding, ultrasonic welding, friction adjustment (tension adjustment), adhesives or, in the case of certain substrates, for example, glass, or rigid semi-rigid and non-rigid polymer substrates, a natural adhesion of the two components.

An exemplary device as described herein is illustrated in Figure 5. The device 100 times is also referred to herein as a cartridge 100. The device 100 comprises a housing 130 with sites for accommodating 121 'analysis units and reagent units. 103, 122, 124, 125. In the exemplary embodiment of Figure 5, analysis units 121 occupy a central host row 130 of device 100. Analysis units 121 may optionally include at least one calibration unit 126. In one example , analysis units 121 are similar to pipette tips and are referred to as analysis tips 121 and calibration units 126 are referred to as calibration tips 126 herein, however, analysis units 121 may be of any form and size as they are widely accommodated by a device 100 as described herein. The analysis units 121 and calibration units 126 are exemplary analysis units 121 and are described in more detail herein. The analysis units 121 in Figure 5 may comprise a capture surface and are suitable, as; for example, to perform a chemical reaction, such icorao nucleic acid analysis and immunoanalysis. The analysis units of 121 can be assembled in the housing according to the instructions or analysis that a user wishes to perform on a sample.

As shown in Figure 5, the housing of the device 100 may comprise a sample collection unit 110 configured to contain a sample. A sample, such as a blood sample, may be placed in the sample collection unit 110. A sample tip 111 (e.g., a pipette tip that attaches to a fluid transfer device as described above). herein) may distribute the sample another housing portion 130. When an assay is to be performed the sample tip 111 may distribute the sample to the pretreatment reagent units or pretreatment units 103, 104, 105, 106, 107, or units of analysis 121. Exemplary pretreatment units 103, 104, 105, 106, 107 include but are not limited to: mixing units 107, diluent units or dilution units 103, 104, and, if the sample is a sample of blood, plasma removal or recovery units 105, 106. The pretreatment units 103, 104, 105, 106, 107 may be of the same type of unit or different types of units. Other pretreatment units 103, 104, 105, 106, 107 as necessary to carry out a chemical reaction can be incorporated into the device 100, as would be obvious to one skilled in the art with knowledge of this relief. The units 103, 104, 105, 106, 107 may contain various amounts of reagents or flexible diluents to what is needed to carry out the analysis of the current cartridge 100.

Frequently, the analysis units 121 can be manufactured separately from the housing 130 and then inserted into the housing 130 with pick and place methods. The analysis units 121 can be adjusted to the constriction 130 or can loosely fit the housing 130. In some embodiments, the housing 130 is manufactured in such a way that it contains the 103 reagent units, 122, 124, 125 and / or analysis units 121 tightly in place, for example during endolaje or manipulation of a cartridge. The Reagent units 103, 122, 124, 125 are shown in Figure 5 which contain a conjugate reagent 122 (eg, for use with, an immunoassay), a wash reagent 125 (eg, to wash the conjugate of the capture surfaces), and a substrate 124 (e.g., an enzyme substrate). Other embodiments of the device 100 and the components in the example of Figure 5 are described herein. Units reagent chi 103, 122, 124, 125 can be manufactured and filled separately from the housing 130 and then placed in the housing '130. In this way, a cartridge 100 can be constructed in a modular manner, thereby increasing the flexibility of the cartridge 100 to be used for a variety of analysis. The reagents in a reagent unit 103, 122, 124, 125 can be chosen according to the analysis to be put into operation. Reagents and exemplary analyzes are described herein.

. A device, such as the example shown in Figure 5, may also comprise other elements as necessary to carry out a chemical reaction. For example, if the analysis units 121 are analysis tips 121 as described herein, the device may comprise tip contact bearings 112 for removing excess sample or reagent from an analysis tip 121 or a sample tip 111 after the fluid transfer, for example, by a system as described herein. The housing 130 may also comprise units or areas 101, 102 between the units of the device 100 for placing a tip or used unit, for example, in order to avoid cross-contamination of a sample tip 111 or analysis unit 121. In Figure 5, the device 100 comprising a sample tip 111 for transferring a sample between the units of the device 100. The device 100 as illustrated in Figure 5 also comprises a pretreatment tip 113 for transferring a sample that has been pretreated in a unit of the device 100 to other units of a device 100 to effect a chemical reaction. For example, the tip sample 111 can be used to draw a blood sample from the sample collection unit 110 and transfer the blood sample to pretreatment units 103, 104, 105, 106, 107 as described. The red blood cells can be removed from the blood sample in the pretreatment units 103, 104, 105, 106, 107 and the pretreatment tip 113 can then be used to collect the blood plasma from the pretreatment units 03, 104, 105, 106, 107 and transferring the blood plasma to another pretreatment unit (e.g., a diluent unit) 103, 104, 105, 106, 107 and / or at least one analysis unit 121. In one embodiment, a sample tip 111 is the sample collection unit 110. In another embodiment, the sample collection unit 110 is similar to a cavity and is configured to contain a sample is received by 1 user.

Analysis units 121 and the reagent units 103, 122, 124, 125 as shown in Figure 5 can be addressable to indicate the location of the units in the cartridge 100. For example, a column of the cartridge 100, as shown in FIG. shown in Figure 5 may contain an analysis unit 121 for carrying out an analysis configured to detect C-reactive protein, and the column may contain corresponding reagent units 103, 122, 124, 125 for analysis in the same column, where the units are addressed to correspond to each other. For example, the address can be entered and stored in a computer system, and the cartridge 100 can be given a label, such as a bar code. When the barcode of the cartridge 100 is scanned for use, the computer system may send the addresses of the units to a system, such as those described herein, to transfer the fluids and to operate a reaction in accordance with the addresses entered into the computer. The addresses can be part of a protocol sent to put the system into operation. The addresses can be in any configuration and can be altered if necessary to change the protocol to carry out an analysis, which in turn can offer a change in the analysis protocol or steps to a user of the cartridge that were not commonly available in POC devices of prior art. In some embodiments, the housing 130 and units are configured in an array of units of 6 by 8 as shown in Figure 5. The physical arrangement of the units can be of any format, for example, rectangular arrays or random physical arrangements. A cartridge 100 can comprise any number of units, for example between 1 and approximately 500. In some embodiments, a cartridge 100 has between 5-100 units. As an example, as shown in Figure 5, the cartridge 100 has 48 units.

Two side cut views of exemplary device 200 of Figure 5 are illustrated in Figures 6A and 6B. A cavity may be formed in a housing 220 of a device for accommodating analysis units (e.g., analysis tips) 201 in a vertical orientation (horizontal housing) with its protuberances toward the top of the device 200. As shown in FIG. Figure 6, a cavity may also be formed to accommodate a reagent unit 210, 212 or a concealed sample collection unit 202. There may be elements in the housing 220 to accurately capture the units and maintain them safely. Such elements may also be designed to operate with a mechanism for moving the tips, such as pick and drop tips. In another embodiment, the sample collection unit comprises a foldable or rotatable element that serves to protect a small collection tube during packaging and to have a. plunger device in place inside a capillary. As shown in Figure 6A there are two exemplary embodiments of reagent units 210, 212 as described herein. The bottom of the housing 220 may be configured to collect liquids or waste, for example, washing reagents after use, which are transferred back through a hole in the housing 220 to the bottom. The housing 220 may comprise an absorbent bearing for collecting waste fluids. The analysis units 201 and sample units 202 can be positioned to fit through a cavity the housing 220 of the device 200 and extend beyond an internal support structure. The reagent units 210, 212 press fit the housing as shown in Figure 6 and do not extend beyond the internal support structure. The housing 220 and the areas in which the analysis units 201 and reagent units 210, 212 can be maintained and placed can be adapted to a variety of patterns.

In some embodiments, each tip provides for a single analysis and may be paired with or correspond to an appropriate reagent, such as reagents required to put the designated analysis into operation. Some tips provide units of control analysis' have known quantities of analyte linked to their capture surfaces, either in the manufacturing process or during the execution of an analysis. In the case of a witness analysis unit, the unit is configured to perform a witness analysis for comparison. The control analysis unit may comprise, for example, a capture surface and analyte which are in solid or liquid state.

In many modalities, the device maintains all the reagents and liquids required by the analysis. For example, for a luminogenic ELISA assay the reagents within the device may include a sample diluent, capture surfaces (eg, three capture antibodies), a detector conjugate (eg, three enzyme-labeled antibodies), a solution of washing, and an enzyme substrate. Additional reagents can be provided as necessary.

In some embodiments, the reagents can be incorporated into a device to provide sample pretreatment. Examples of pretreatment reagents include, without limitation, white cell lysis reagents, reagent lysis reagents of cell-removing red blood cells, reagents for analytes releasing binding factors in the sample, enzymes and detergents. The pretreatment reagents can also be added to a diluent contained within the device.

An individual reagent unit can configure a sample to receive a movable analysis unit. In some embodiments, the individual analysis unit comprises a hollow cylindrical open ended element comprising a capture surface and a reaction cuvette. Cylindrical analysis unit can be determined as tip analysis in the present. In some embodiments, the individual analysis unit is configured to perform an immunoassay. One unit of analysis comprises a small tip or tubular formation is in Figure 7A. In some instances, the tip 301 is configured to provide an interior cylindrical capture surface 311 and a protuberance 321 capable of engaging the housing of the device. In some instances, the protrusion .321 and the tip 301 is configured to engage with a tip moving mechanism 301,. such as a system as described herein or for example, a fluid transfer device. An analysis tip 301, shown in Figure 7A may comprise an opening 331 in the bottom of the tip. The opening 331 can be used to transfer fluids or reagents in and out of an analysis unit 301. In. A mode j1, an analysis unit 301 as described is or similar to a pipette tip with the improvement that the analysis unit of 301 comprises a capture surface 311 configured to detect an analyte in a sample.

The tip 301 can be manufactured by an injection molding process. In one embodiment, tip 301 is fabricated from a refined polystyrene for use with chemiluminescence analysis. As shown in Figure 7A, an exemplary tip 301 comprises a protrusion (such as the larger upper half of the tip 301), which can be engaged with a housing and which can be coupled, for example, with tapered elements of a device; of fluid transfer and / or pipetting devices to form a frantic pressure seal. Also shown in Figure 7A, the exemplary tip 301 comprises a smaller cylindrical part. In many embodiments, an analysis capture surface is contained in the smallest cylindrical part. The analysis capture surface can be anywhere within the tip 301 or on the outside of the tip 301. The surface of the tip 301 can be of many geometries including, but not limited to, cubic tubular, or pyramidal. In analyzes other than chemiluminescence and fluorescence based on the tip 301 can serve as a convenient means to present the analytical product to the optical elements of the analysis.

Figure 7B demonstrates an exemplary sample collection unit 302 comprising a sample tip: 302. The sample tip 302 as shown in Figure 7B may also be separated from a sample collection unit 302 and used to transfer the sample from the sample collection units to other units in a device as described herein. The sample tip as shown in Figure 7B comprises a protrusion 300x2 as described herein for coupling the tip 302 with a housing of a device and a fluid transfer device. The sample tip 302 also comprises an opening 332 to allow the transfer of fluids or samples in and out of the sample tip. In some embodiments, the sample tip 302 is in the same way as an analysis tip. 301. In other embodiments (such as those shown in Figures 7A and 7B), the sample tip 30.2 is in a different manner than the analysis tip 301.

In one embodiment, a function of the tip is to allow liquid samples and reagents to be brought into contact with the capture surface of the analysis unit. Movement can occur through a variety of means including, but not limited to, capillary action, aspiration and controlled pumping. The small size of the tips allows rapid control of the referred temperature for a chemical reaction. The transfer of heat and / or maintenance can be carried out by simply placing the tip in a controlled temperature block or chamber.

In some embodiments, the tip is capable of containing approximately 1 to 40 microliters of fluid. In a further embodiment, the exact tip may contain from 5 to 26 microliters of the fluid. In one embodiment, the tip contains 20 microliters of the fluid. In some instances, the tip may contain one microliter of fluid or less. In other instances, the tip may contain up to 100 microliters i Wherever desired, the end of the tip can; to be applied on an absorbent material (for example incorporated in a disposable cartridge) before the introduction of the customer analysis component to avoid contamination with a small amount of sample and / or reagent.

Due to physical forces, any liquid extracted to a subject tip can be maintained at any desired location with minimal risk of liquid draining, even when maintained in a vertical orientation. The analysis unit (for example, an analysis tip) can be covered with analysis capture reagents before use, using similar fluids as in the analysis (for example, controlled capillary or mechanical aspiration).

A capture surface (also referred to herein as a reaction site) can be formed by a binding antibody or other capture reagents covalently linked or by absorption to the analysis unit. The surface can then be dried and kept in a dry condition until it is used in an analysis.

In one embodiment, there is a reaction site for each analyte to be measured.

In one embodiment, the analysis unit can be moved in fluid communication with the reagent unit and / or a sample collection unit, such that a reagent or sample can interact with a reaction site where linked probes can detect an analyte of interest in the body fluid sample. A reaction site can then provide a signal indicating the presence or concentration of analyte of interest, which can then be detected in a detection model described herein.

In some modalities, the location and consideration of a reaction site is an important element in an analysis device. Most, if not all, of the immunoassay devices have been configured with capture surfaces as an integral part of the device.

In one embodiment, a molded plastic analysis unit is either commercially available or can be manufactured by injection molding with price shapes or sizes. For example, the characteristic dimension can be a diameter of 0.05-3 mm or it can be of a length of 3 to 30 mm. The units can be covered with capture reagents using a method similar to those used to coat microtiter plates, but with the advantage that they can be processed in bulk by placing them in a large container, adding coating reagents and processing using screens, carriers and the like to recover the pieces and wash them as; be necessary .

The analysis unit can offer a rigid support on which a relative can be immobilized. The unit of analysis is also chosen to provide appropriate characteristics with respect to light interactions. For example, the analysis unit can be made of a material, such as functionalized glass, copy formula, modified silicon or any of a wide variety of gels' or polymers such as (poly) tetrafluoroethylene, (poly) vinylidene difluoride, polystyrene, porlicarbonate, polypropylene, pma, abs or combinations thereof. In one embodiment, an analysis unit comprises polystyrene, other materials may be used in accordance with the present invention. A reaction device can be advantageous. Furthermore, in the case where there is an optically transmitting window that allows light to reach an optical detector, the surface may advantageously be opaque and / or preferably light scattering.

A reagent immobilized on the capture surface can be anything useful for detecting an analyte of interest in a body fluid sample. For example, such reagents include, significance, nucleic acid probes, antibodies, cell membrane receptors, monoclonal antibodies and antisera reactive with a specific analyte. Several commercially available reagents such as a polyclonal and monoclonal antibody host developed specifically for specific analytes can be used.

The experienced in the art will appreciate that there are many ways to immobilize various assets on strong use where the reaction can take place. The immobilization can be covalent or non-covalent, via a linker moiety or attached to an immobilized portion. Exemplary non-limiting bonding moieties for attaching either nucleic acid or proteinaceous molecules such as antibodies to a solid support include structobyrin or ambilene / morphine linkage, carbonate linkages, ester, amine, thioester, thiourea (N) -Functionalized linkages, functionalized maleimide, amide, bisulfur, amide, hydrasuna bonds among others. In addition, a portion of ciuril can be attached to a direct nucleic acid to a substrate such as glass using methods known in the art. The surface immobilization can also be obtained via a poly-l-licina fastener, which provides a load-load accommodation to the surface.

The units of analysis can be dried immediately after the last stage of incorporating a capture surface. For example, drying can be effected by massive exposure to an atmosphere or via the use of a vacuum manifold and / or the application of secolid air by means of a manifold.

In many modalities, a unit of analysis is designed to allow the unit to be manufactured in a rapid high-volume manufacturing process. For example, the beads can be assembled in large-scale arrays for batch coating the capture surface or on the tip. In another example, the tips can be placed on a moving band or rotary table for serial processing. In yet another example, an array of tips can be connected to vacuum and / or pressure manifolds for simple processing.

In one embodiment, an analysis unit can be operatively coupled by a fluid transfer device. The fluid transfer device can be put into operation under automatic control without human interaction. In units of analysis comprising tips, the control of the installed height of a disposable liquid tip depends on. Attachment of interference to used from tip to liquid spout. A fluid transfer device can be coupled with the tip. In some instances, the length of immersion of a tip in liquid to be transferred must be known to initialize the contact of the liquid with the outside of the tip which can be uncontrolled. In order to isolate or adhere a tip to the fluid transfer device, a live obstacle may be shown at the bottom of the used connector that engages with the nozzle of the jet. An air seal that can be made using a gasket halfway through the use or on the flat bottom of the nozzle. By separating the seal position from the controlled height of the tip both can be adjusted separately. The fluid transfer device can allow many analyzes to be performed in parallel.

Reagent units of a badge can store assets that are required to carry out a given reaction to detect a given analyte of interest. Liquid reagents can be supplied in small capsules that can be manufactured from a variety of materials including, without imitation plastic such as polystyrene, polypropylene or polypropylene. In some embodiments, the reagent units are cylindrical cups. Two examples of a reagent unit 401, 402 comprising a cup are shown in Figures 8 A and 8 B. Where desired, the units 401, 402 adjust the pressure to the cavities to a housing of a device. The units 401, 402 can be sealed on the open surface to prevent spillage of reagent 411, 412 on board. In some embodiments, the seal is an aluminized plastic and can be sealed to the cup by thermal bonding. A unit can be in any form as necessary to contain a reagent. For example, a cylindrical reagent unit 401 is shown. in Figure 8A and the reagent unit contains a liquid reagent 411. A differently shaped reagent unit 402 is illustrated in Figure 8B also contains a liquid reagent 412. Both exemplary 401, 402 comprise slight optional modifications near the surface upper that allow the units 401, 402 to snap into a housing of a device as described herein.

In many embodiments of the invention, the reagent units are modular. The reagent unit can be designed to allow the unit to be manufactured in a high volume rapid manufacturing process. For example, many reagent units can be filled and sealed in a large-scale process simultaneously. The reagent units can be filled according to the type of analysis or analysis to be put into operation by the device. For example, if a user wants different analyzes than another user, the reagent units can be manufactured according to the preference of each user, without the need of manufacturing the entire device. In another example, the reagent units can be placed in a moving band or rotating table for serial processing.

In another embodiment, the reagent units are accommodated directly in cavities in the housing of a device. In this mode, a stamp can be made on the accommodation areas surrounding the units.

Reagents according to the present invention include, without limitation, washing buffer solutions, enzyme substrates, dilution buffer solutions, conjugates, enzyme-labeled conjugates, DNA amplifiers, sample diluents, wash solutions, reagents sample pre-treatment including additives such as detergents, polymers, chelating agents, albumin binding reagents, enzyme inhibitors, enzymes, anticoagulants, red blood cell binding agents, antibodies or other materials necessary to carry out an analysis in a device An enzyme-labeled conjugate can be either a polyclonal antibody or monoclonal antibody labeled with an enzyme that can produce a detectable signal after reaction with an appropriate substrate. Non-limiting examples of such enzymes are alkaline phosphatase and horseradish peroxidase. In some embodiments, the reagents comprise immunoassay reagents. In general, reagents, especially those that are relatively unstable when mixed with liquid, are confined separately in a defined region (e.g., a reagent unit) within the device. 1 In some embodiments, a reagent unit contains about 5 microliters to about 1 milliliter of liquid. In some embodiments, the unit may contain approximately 20-200 microliters of liquid. In a further embodiment, the reagent unit contains 100 microliters of fluid. In one embodiment, a reagent unit contains approximately 40 microliters of fluid. The volume of liquid in a reagent unit can vary depending on the type of analysis that is carried out or the body fluid sample provided. In one embodiment, the volumes of the reagents do not have to be predetermined, but they must be more than a known minimum. In some embodiments, the reagents are initially stored dry and dissolved after the start of the analysis that is carried out on the device.

In one embodiment, the reagent units can be filled using a siphon, a funnel, a pipette, a syringe, a needle or a combination thereof. The reagent units can be filled with liquid using a filler channel and a vacuum extraction channel. The reagent units can be filled individually or as part of a global manufacturing process.

In one embodiment, a single reagent unit comprises a different reagent as a means of isolating reactants from each other. The reagent units can also be used to contain a wash solution or a substrate. In addition, the reagent units can be used to contain a luminogenic substrate. In another embodiment, a plurality of reagents are contained within a reagent unit.

In some instances, the assembly of the device allows the pre-calibration capability of analytical units and the reagent units prior to the disposable assembly of the subject device.

In one aspect, a FS system of the invention comprises a device comprising analysis units and reagent units comprising reagents (both liquid phase and solid phase reactants). In some embodiments, at least one of the entire device, a unit of analysis, a unit of reagent or a combination thereof, is disposable. In a system of the invention, the detection of an analyte with a device is put into operation by an instrument. In most modalities, the instrument, device and method offer an automated detection system. The automated detection system can be automated based on a defined protocol or a protocol provided to the system by the user.

In one aspect, a system for the automated detection of an analyte in a body fluid sample comprises a device or cartridge and detection or detector to detect the Indicator of the presence or absence of the analyte.

In one modality, the user applies a sample (for example, a measured or unmeasured blood sample;) to the device and insert the device into the instrument. All subsequent stages are automatic, already programmed, "either by instrument (wiring), the user, a user or remote system or modification of the operation of the instrument according to an identifier (for example, a barcode or RFID in the device) .

Examples of different functions that can be carried out using a system of the invention include, but are not limited to, dilution of a sample, removal of parts of a sample (e.g., blood-blood globules (RBC)), react a sample in a unit of analysis, add liquid reagents to the sample and unit of analysis, wash the reagents of the sample and unit of analysis and contain liquids during and after use! Of the device. . The reagents may be on board the device in a reagent unit or in a reagent unit to be assembled to the device. I, An automated system can detect a particular analyte in a biological sample (eg, sarlgre) by an enzyme-linked immunosorbent assay (ELISA). The system is prone to multiplexing and is particularly suitable for detecting an analyte of interest present in a small volume of whole blood sample (eg, 20 microliters or less). The system can also detect analytes in different dilutions of a single sample, allowing different sensitivities to be tested in the same device, when desired. All reagents, supplies and waste can be contained in the system device.

In use, a sample of a subject is applied to the assembled device and the device is inserted into an instrument. In one embodiment, an instrument can begin sample processing by some combination of removal of red blood cells (blood sample), dilution of the sample, and movement of the sample to the unit of analysis. In a multiplexed analysis mode, a plurality of analysis units are used and a portion of the sample is moved to individual analysis units in sequence or in parallel. The analyzes can then be performed by a controlled sequence of incubations and applications of reagents to the capture surfaces.

An exemplary fluid transfer device consists of any component capable of making precise and accurate fluid movements. Examples of components include, but are not limited to, pumps for sucking and ejecting known volumes of fluid accurately from cavities or units of the device, at least one step of translation to improve the precision and accuracy of movement within the system. The system also comprises a detector for detecting a signal generated by a signal generator (such as an enzyme in contact with its substrate) in a unit of analysis. The detectors include PMT, diode, CCD and the like. In the case of analysis based on absorbance or fluorescence, a light source is used. For luminescence-based analysis, the light source in the system instrument is not needed and an Avalanche PMT or photodiode detector can be used. Wherever desired, the instrument has temperature regulation to provide a regulated temperature environment for incubation analysis. In one embodiment of the invention, the instrument controls the temperature of the device. In a further embodiment, the temperature is in the range of about 30-40 ° C. In some embodiments, the temperature control by the system may comprise active cooling. In some instances, the temperature range is approximately 0-100 ° Celsius. For example, for nucleic acid analysis, temperatures of up to 100 ° Celsius can be obtained. In one modality, the interval of. temperature is approximately 15-50 ° Celsius. A system temperature control unit may comprise a thermoelectric device, such as a Peltier device.

Cartridges, devices and systems as described herein may offer many elements that are not available in existing POC systems or integrated analysis systems. For example, many POC cartridges rely on a closed fluid loop system to handle small volumes of liquid efficiently. The cartridges and fluid devices described herein may have open fluid movement between cartridge units. For example, a reagent can be stored in a unit, a sample in a sample collection unit, a diluent in a diluent unit, and the capture surface can be in a unit of analysis, wherein in a cartridge stage, none of the units are in fluid communication with any of the other units. Using a device or fluid transfer system as described herein, the analysis units do not have to be in fluid communication with each other. This can be advantageous in some installations because each analysis chemistry does not interact physically or chemically with others to avoid interference due to cross-talk analysis. The units can be movable with each other in order to bring some units in fluid communication. For example, a fluid transfer device may comprise a head that couples with an analysis unit and moves the analysis unit in fluid communication with a reagent unit.

The devices and systems herein can provide an effective means for high-throughput, real-time detection of analytes present in a body fluid of a subject. Detection methods can be used in a wide variety of circumstances including identification and quantification of analytes that are associated with specific biological processes, physiological conditions, alterations or alteration stages. As such, the systems have a broad spectrum of utility in, for example, drug selection, disease diagnosis, phylogenetic classification, parental and forensic identification, disease onset and recurrence, individual response to treatment versus population bases, and therapy monitoring. The present devices and systems are also particularly useful for the preclinical and advanced clinical stage of therapeutic development, improving patient compliance, monitoring of ADRs associated with a prescribed drug, development of individualized medicine, provision by third parties of blood tests of central laboratory at home or on a basis of prescription and monitoring of therapeutic agents immediately after regulatory approval or during clinical trials. The devices and systems can provide a flexible system for personalized medicine. Using the same system, a device can be changed or exchanged together with a protocol or instructions to a programmable processor of the systems to perform a wide variety of analyzes as described. The systems and devices herein offer many elements of a laboratory installation in a desktop-sized or smaller automated instrument. Due to these elements, the devices are particularly suitable for deployment as FS devices for the HS systems of the invention.

In some embodiments, an individual to be monitored by the HS is provided with a plurality of devices to be used to detect a variety of analytes. An individual can for example use different fluid devices on different days of the week. In some embodiments, the programming elements in the external device that associate the identifier with a protocol may include a process for comparing the current day with the day in which the fluid device is to be used based on a clinical test for example . In another embodiment, the individual is provided with different reagent units and units of analysis that can fit into a housing of a device interchangeably. In yet another modality, as described, the individual does not need a new device for each test day, but rather, the system can be programmed or reprogrammed when downloading new instructions from, for example an external device such as a server. If, for example, the two days of the week are not identical, the external device can wirelessly notify the individual using any of the methods described herein or known in the art to notify them of the appropriate device and / or instructions appropriate for the system. . This example is only illustrative and can easily be extended to, for example, notifying a subject that a device. Fluid is not being used at the correct time of day. Using these methods, FS devices can be quickly adjusted as the disease is monitored. For example, the OS can direct the FS to immediately analyze individuals in contact with an index case.

In a . embodiment, a cartridge as illustrated in Figure 5 comprises a variety of analysis units and reagent units. The analysis units may comprise a capture surface according to an analyte to be detected. The analysis units can then be assembled with the rest of the device just in time. In many POC devices of the prior art, the capture surface is integral to the device and if the capture surface is incorrect or not properly formed, the entire device may operate inappropriately. By using a device as described herein, the capture surface and / or analysis unit can be individually controlled and individually fabricated independently of the reagent units in the device housing.

The reagent units can be filled with a variety of reagents in a just-in-time manner. This provides flexibility of the device because it can be made. In addition, the reagent units can be filled with different volumes of reagents without affecting the stability of the device or the chemical reactions that are to be carried out within the device. Coupled with a system as described with a fluid transfer device, the devices and units described herein offer flexibility in the methods and protocols of the analyzes to be carried out. For example, a batch of similar devices that contain the same reagents can be given to a community that is monitored by the HS. After a monitoring period, the OS identifies that the analysis could be optimized by changing the dilution, the sample and the amount of reagent provided to the unit of analysis. As stipulated herein, the analysis can be changed or optimized by simply changing the instructions to a programmable processor of the fluid transfer device. For example, the batch of cartridges in the patient's bottom has excess diluent loaded on the cartridge. The new protocol requires four times as much diluent as the previous protocol. Due to the methods and systems provided herein, the protocol can be changed in the central OS server and sent to all systems to execute the methods with the devices without having to provide new devices to the patient's bottom. In other words, the POC device and system as described herein can offer much of the flexibility of a standard laboratory practice where excess reagents and often excess samples are frequently available. Such flexibility can be obtained without compromising the advantages of the POC testing scenario or the ability to analyze small sample volumes.

In some instances, where the cartridge units are separated, the devices and systems provide flexibility in construction of the systems described herein. For example, a cartridge may be configured to perform 8 analyzes using an array of analysis units and an array of reagent units. Due to the elements of the cartridge as described herein, the same housing or a housing of the same design can be used for the manufacture of a cartridge: with up to 8 different analyzes than the previous cartridge. This flexibility is difficult to obtain in many other designs of the POC device due to closed systems and fluid channels and therefore, the devices may not be modular or as easy to assemble as described.

Currently, there is a need to detect more than one analyte wherein the analytes are present in a widely variable concentration range, for example, one analyte is in the pg / ml concentration range and another is in the concentration range of the analyte. xq / l. In a non-limiting example, a viral antigen can be detected in the pg / ml range while a host antibody to that antigen is detected in the pg / ml range. See Table 4. The system as described herein has the ability to. Analyze simultaneously analytes that are present in the same sample in a wide concentration range. Another advantage is being able to detect concentrations of different analytes present in a wide concentration range is the ability to relate the proportions of the concentration of these analytes with the safety and efficacy of multiple drugs administered to a patient. For example, unexpected drug-drug interactions can be a on cause of adverse drug reactions. A concurrent real-time measurement technique to measure different analytes would help avoid the potentially disastrous consequence of adverse drug-drug interactions. This can be useful when drugs are rapidly deployed to control an outbreak.

Being fit of. monitor the rate of change of an analyte concentration and / or concentration of pharmacodynamic (PD) or pharmacokinetic (PK) markers over a period of time in a single subject or perform trend analysis on the concentration or markers of PD or PK, and Whether they are drug concentrations or their metabolites, it can help prevent potentially dangerous situations. For example, if the HS is used to monitor diabetes and glucose were the analyte of interest, the concentration of glucose in a sample at a given time, also as the rate of change of the glucose concentration in a given period of time could be highly useful for predicting and avoiding, for example, hypoglycemic events. Such trend analysis has broad beneficial implications in the drug dosage regimen. When multiple drugs and their metabolites are concerned, the ability to point a trend and take proactive measures is often desirable.

Thus, the data generated with the use of the fluid devices and systems present can be used to perform a trend analysis on the concentration of an analyte in a subject.

Frequently, multiple analyzes in the same cartridge may require different dilutions or pre-treatments. The dilution interval can be substantial between analyzes. Many current POC devices offer a limited dilution range and therefore a limited number of analyzes can potentially be carried out on the POC device. However, a system and / or cartridge as described herein may offer a large range of dilutions, for example, 1: 2-1: 10,000 due to the ability of the system to serially dilute a sample. Accordingly, a large number of potential analyzes can be performed, in a single cartridge or a plurality of cartridges without modifying the detector or reading instrument for the analyzes.

In one example, a system as provided herein is configured to perform multiple detection analyzes of different target analytes (e.g., five or more). In order to bring the expected analyte concentration within the detection range of an immunoassay as described herein and commonly used in the POC field, a sample must be diluted, for example, 3: 1, 8: 1, 10: 1, 100: 1 and 2200: 1, to carry out each of the five analyzes. Because the fluid transfer device is able to contain and In order to move the fluid within the device, serial dilutions can be made with a system as described herein to obtain these five different dilutions and detect all five different target analytes. As described above, the protocol for performing the analyzes is also apt to be adjusted without modifying the device or the system.

In a laboratory facility with traditional pipetting, commonly larger sample volumes are used than in a POC team. For example, a laboratory can analyze a sample of blood drawn from a patient's arm in a volume in the milliliter range. In a POC team, many devices and users demand that the process be fast, easy and / or minimally invasive, therefore, small samples (of the order of a volume in the microliter range) such as that obtained by a finger prick ) are commonly analyzed by a POC device. Due to the difference in sample, current POC devices may lose flexibility in carrying out an analysis that is offered in a laboratory facility. For example, to carry out multiple analyzes of a sample, a certain minimum volume may be required for each analysis to allow the accurate detection of an analyte, therefore, by placing some limits on a device in a POC equipment.

In another example, a system and / or fluid transfer device as described herein provides a lot of flexibility. For example, the fluid transfer device can be automated to move an analysis unit, an analytical tip or an empty pipette from a unit of the device to a unit separate from the device, not in fluid communication with each other. In some instances, this can prevent cross-contamination of the units of a device as described. In other instances, it allows for the flexibility of moving various fluids within a device as described in contact with each other in accordance with a protocol or instructions. For example, a cartridge comprising 8 sets of different reagents in 8 different reagent units can be addressed and coupled by a fluid transfer device in any order or combination as instructed by the protocol. Accordingly, many different sequences can be carried out for any chemical reaction carried out on the device. Without changing the volume of reagents in the cartridge or the type of reagents in the cartridge, the analysis protocol may be different or modified without the need for a second cartridge or a second system.

For example, a FS worker orders a cartridge, with a specific type of capture surface and specific reagents to carry out an analysis to detect an analyte (eg, C-reactive protein (CRP)) in a sample. The protocol that the FS worker originally planned may require 2 stages of washing and 3 stages of dilution. After the FS worker has received the system and device, those on the OS site responsible for the deployed FS devices determine that the protocol must have 5 stages of washing and only 1 stage of dilution. The devices and systems herein can allow for flexibility in this protocol change without having to reconfigure the device or system. In this example, only a new protocol or set of instructions need to be sent from the OS component to the programmable processor of the FS system or the fluid transfer device.

In another example, a system as provided herein is configured to perform five different target analyte detection assays, wherein each assay needs to be incubated at a different temperature. In many POC devices of the prior art, the incubation of multiple analyzes at different temperatures is a difficult task because the multiple analyzes do not. they are modular and the capture surfaces can not be moved relative to the heating device. In a system as described herein, wherein an individual analysis unit is configured to perform a chemical reaction, an individual analysis unit may be placed in an individual heating unit. In some embodiments, a system comprises a plurality of heating units. In some instances, a system comprises at least as many heating units as units of analysis. Accordingly, a plurality of analyzes can be carried out as a plurality of temperatures.

The systems and devices as described herein may also provide a variety of quality control measures not previously available with many POC devices of the prior art. For example, due to the modularity of the device, the analysis units and reagent units can be controlled in quality separately from each other and / or separately from the housing and / or separately from a fluid transfer system or device. Exemplary quality control methods and systems offered by the systems and devices herein are described.

A FS system as described for use with the invention can carry out a variety of analysis, regardless of the analyte that is detected from a body fluid sample. A protocol dependent on the identity of the device can be transferred from the external OS component where it can be stored to a reader set to allow the reader set to carry out the specific protocol on the device. In some embodiments, the device has an identifier (ID) that is detected or read by an identifier detector described herein. The identifier detector can communicate with a communication set via a controller that transmits the identifier to an external device. Wherever desired, the external device sends a protocol stored in the external device to the communication set based on the identifier. The protocol to be carried out in the system may comprise instructions to the system controller to carry out the protocol, including but not limited to a particular analysis to be carried out and a detection method to be performed. Once the analysis is performed by the system, a signal indicating an analyte in the body fluid sample is generated and detected by a system detection set. The detected signal can then be communicated to the set of communications, where it can be transmitted to the external device for processing, including without limitation, calculation of the analyte concentration in the sample.

In some embodiments, the identifier may be a bar code identifier with a series of black and white or reflective lines or blocks, which may be read by an identifier detector such as a bar code reader, which are well known or a radio frequency identification (RFID) tag with an appropriate detector. Other identifiers could be a series of 'alphanumeric values, colors, raised protuberances or any other identifier that may be located on the device and be detected or read by an identifier detector. The identifier detector may also be an LED that emits light that can interact with an identifier that reflects light and is measured by the identifier detector to determine the identity of a device. In some embodiments, the identifier may comprise a storage device or memory device and may transmit information to an identification detector. In some modalities, a combination of techniques can be used. In some embodiments, the detector is calibrated by the use of an optical source, such as an LED.

In one example, a sample of body fluid can be provided to the device and the device can be inserted into a system. In some embodiments, the device is partially inserted manually and then a mechanical switch in the reader assembly appropriately automatically places the device inside the system. Any other mechanism known in the art for inserting a disk or cartridge into a system can (be used.) In some embodiments, manual insertion may be required.

In some embodiments, a method for automatically selecting a protocol may be put into operation in a system comprising providing a device comprising an identifier detector and an identifier; detect the identifier; transferring the identifier to the external OS component of the systems of the invention; and selecting a protocol to be operated in the system from a plurality of protocols in the external OS component associated with the identifier. i In one embodiment, a FS system of the invention for automated detection of a plurality of analytes in a body fluid sample comprises: a fluid device (such as those described herein) comprising: a sample collection unit configured to contain the body fluid sample; an array of analysis units, wherein an individual analysis unit of the array of analysis units is configured to carry out a chemical reaction that produces a signal indicating an individual analyte of the plurality of analytes that are detected; and an array of reagent units, wherein a single reagent unit of the reagent unit array contains a reagent. The system further comprises a fluid transfer device comprising a plurality of heads, wherein an individual head of the plurality of heads is configured to be coupled to the individual analysis unit and wherein the fluid transfer device comprises a programmable processor configured to direct the transfer of fluid from the body fluid sample from the sample collection unit and the reagent from the individual reagent unit to the individual analysis unit. For example, an individual analysis unit comprises a reagent and is configured to carry out a chemical reaction with that reagent.

In some instances, the processor configuration to direct the fluid transfer effects a degree of dilution of the body fluid sample in the array of analysis units to bring signals indicating the plurality of analytes that are detected within a detectable range, such that the plurality of analytes are detectable with the system. In an example, the body fluid sample comprises at least two analytes that are present at concentrations that differ by at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 50 or 100 orders of magnitude . In one example, the body fluid sample is a single drop of blood. In one embodiment, the concentrations of at least two analytes present in a sample differ by up to 10 orders of magnitude (for example, a first analyte is present at 0.1 pg / ml and the second analyte is present at 500 pg / ml). In another example, some protein analytes are found at concentrations greater than 100 mg / ml, which can extend the range of interest to approximately twelve orders of magnitude.

A degree of dilution of the body-fluid sample can bring the indicator signals of the at least two analytes within the detectable range. In many instances, a system further comprises a detector, such as a photomultiplier (P T). With a photomultiplier, for example, a detectable range of the detector may be about 10 to about 10 million counts per second. Each count corresponds to a single photon. In some instances, the PMTs are not 100% efficient and the observed counting rate may be slightly lower than, but still close to the actual number of photons arriving at the detector per unit time. In some instances, the counts are measured in approximately ten intervals of approximately one second and the results are averaged. In some modalities, the intervals for analysis are 1000 - 1,000,000 counts per second when a PMT is used as a detector. In some instances, counting speeds as low as 100 per second and counting speeds as high as 10,000,000 are measurable. The linear response range of the PMTs (for example, the interval in which the counting speed is directly proportional to the number of photons per unit time) can be approximately 1000-3,000,000 counts per second. In one example, an analysis has a detectable signal at the lower end of approximately 200-1000 counts per second and at the high end of approximately 10,000-2,000,000 counts per second. In some instances for protein biomarkers, the rate of counting is directly proportional to alkaline phosphatase linked to the capture surface and also directly proportional to the concentration of the analyte. Other exemplary detectors include avalanche photodiodes, avalanche photodiode arrays, CCD arrays, over-cooled CCD arrays. Many other detectors have an output that is digital and generally proportional to the photons that reach the detector. The detectable range for exemplary detectors may be appropriate to the detector that is used.

An individual head of a fluid transfer device can be configured to adhere to the individual analysis unit. The fluid transfer device can be a pipette, such as an air displacement pipette. The device; Fluid transfer can be 'automated. For example, a fluid transfer device may further comprise a motor in communication with a programmable processor and the motor may move the plurality of heads based on a protocol of the programmable processor. As described, an individual analysis unit may be a pipette tip, for example, a pipette tip with a capture surface or reaction site.

Frequently, in a POC device, such as the systems and devices described herein, the dilution factor must be estimated and reasonably accurate. For example, in environments where non-expert users put on or look like the system there is a need for ways to ensure accurate dilution of a sample.

As described herein, a fluid transfer device can effect a degree of dilution of a sample to provide accurate analysis results. For example, a programmable fluid transfer device may have multiple heads to serially dilute or dilute samples, as well as provide a mixture of a sample and diluent. A transfer device ? Fluid can also provide movement of fluid1 in POC devices.

As described, the systems and devices herein can enable many elements of the flexibility of the laboratory installation in a toe environment. For example, samples can be collected and manipulated automatically in a tabletop or smaller size device or system. A common issue in POC devices is to obtain different dilution intervals when a plurality of analyzes are carried out, where the 'analyzes may have a significantly different sensitivity or specificity. For example, there may be two analytes in a sample, but one analyte has a high concentration in the sample and the other analyte has a very low concentration. As provided, the devices as described herein, can dilute the sample to significantly different levels in order to detect both analytes. For example, if the analyte is in a high concentration, a sample can be serially diluted to an appropriate detection range and provided to a capture surface for detection. In the same system or label, a sample with an analyte in a low concentration may not need to be diluted. In this way, the analysis interval of the POC devices and systems provided herein can be expanded from many of the current POC devices.

A fluid transfer device can be part of a system that is a bank instrument. The fluid transfer device may comprise a plurality of heads. Any number of heads as necessary to detect a plurality of analytes in a sample is contemplated for an inventive fluid transfer device. In one example, a fluid transfer device has approximately 8 heads mounted on a line and separated by a distance. In one embodiment, the heads have a used nozzle that is i Coupled by snap fitting with a variety of tips, such as analysis unit or sample collection units as described herein. The tips may have an element that. it allows them to be automatically removed by the instrument and arranged in a housing of a device as described after use. In one embodiment, the analysis tips are clear and transparent and can be similar to a cuvette within which an analysis is carried out that can be detected by an optical detector such as a photomultiplier tube.

In one example, the programmable processor of an FS system may comprise instructions or commands and may operate a fluid transfer device in accordance with the instructions for transferring liquid samples either upon extracting (eg extracting liquid into) or extending (to eject liquid) a piston to a closed air space. Both the volume of air moved and the speed of movement can be controlled precisely, for example, by the programmable processor.

Mixing samples (or reagents) with diluents (or other reagents) can be had by sucking the components to be mixed into a common tube and then repeatedly sucking a significant fraction of the volume of the combined liquid up and down a tip.

The distribution of dry reagents to a tube can be effected in a similar manner. Incubation of liquid and reactive samples with a capture surface on which a capture reagent (eg, an antibody) is bound can be obtained by extracting the appropriate liquid to the tip and keeping it there for a predetermined time. The removal of samples and reagents can be obtained by ejecting the liquid into a tank or onto an absorbent bearing in a device as described. Another reagent can then be extracted to the tip according to the instructions or protocol of the programmable processor.

In an example as shown in Figure 9, the liquid 1111 previously in a tip 1101 can leave a thin film 1113 inside the tip 1101 when it is ejected. Accordingly, a system can use the action of the front portion (eg, the uppermost portion) of the next liquid 1112 to remove the previously present liquid 1111 from the tip 1101. The portion of the subsequent liquid contaminated with the previously present liquid 1113 can being held on top of the tip 1101 where it does not continue to interact with the capture surface 1102. The capture surface 1102 may be in a defined area of the tip 1101, such that the prior liquid 1111. does not react with the capture surface 1102, for example, as shown in FIG. 9, the capture surface 1102 occupies a portion of the defined cylindrical portion of the tip 1101 that does not extend completely to the protrusion of the tip. In many instances, the incubation time is short (for example 10 minutes) and the separation of the contaminated liquid zone is relatively large (copying data) in such a way that the decision of the active components of the contaminated portion of the liquid 1113 does not occurs fast enough reacting with the capture surface 1102 during the incubation. For many high sensitivity analyzes, there is a requirement to remove a reagent or wash the capture surface (for example, a detector antibody that is labeled with the analysis signal generator). In one example, a fluid transfer device of a system described herein can provide washing by adding additional removal and aspiration cycles of fluid transfer, for example using a wash reagent. In one example, four washing steps demonstrated that the unbound detector antibody in contact with the capture surface is reduced by a factor of better than 10 to 6 fold. Any detector antibody not specifically bound to the capture surface (highly initiatable) can be removed during this washing process.

The extension of the interval of an analysis can be carried out by dilution of the sample. The POC analysis system using disposable cartridges containing the diluent there is often a practical limit to the extent of dilution. For example, if a small blood sample is obtained by finger pricking (for example, approximately 20 microliters) it will be diluted and the maximum volume of diluent can be placed in a 250 microliter tube, the maximum dilution limit of all The sample is approximately 10 times. In one example in the present, the system can suck a smaller volume of the sample (for example about 2 ml) making the maximum dilution factor approximately 100 times. For many analyzes, such dilution factors are acceptable but for an analysis such dilution factors are acceptable but for other analysis similar to that of crp (as described in the examples herein) f need to dilute the sample much more. Elisa analysis based on separation may have an intrinsic limitation on the surface capacity of. capture to bind in the analyte (eg, equivalent to about 400 nanograms / ml) in the diluted sample for a typical protein analyte. Some analytes are present in the blood at "hundreds of micrograms / ml." Even though they are diluted 100-fold, the analyte concentration may be outside the calibration range In an exemplary embodiment of a system, fluid transfer device in the present, multiple divisions can be obtained by making multiple transfers of fluid from the diluent to an individual analysis unit or sample collection unit, for example, if the concentration of un-analyte is very high in a sample as described above, the sample can be diluted multiple times until the concentration of the analyte is within the acceptable detection range The systems and methods herein can provide accurate estimates of the divisions in order to calculate the original concentration of the analyte.

In one embodiment, a FS system as described herein can move a sample of the liquid and move a unit of analysis. The system can contain a heating block and a detector. In order to move a liquid sample, the system can provide suction action, syringe or pipette type. In an exemplary embodiment, the fluid transfer device for moving a liquid sample is a pipette and pipette head system. The number of pipette devices required by the system can be adjusted according to the type of analyte to be detected and the number of analyzes that are carried out. The actions carried out by the pipette system can be automated or put into operation manually by a user.

Figure 10 demonstrates an example of a fluid transfer device 520 and system 500 as described herein. The fluid transfer device system can move 8 different or identical volumes of liquids simultaneously using the 8 different heads 522. For example, the cartridge (or device as described herein) 510 comprises 8 units of analysis 501. Units of individual analyzes 501 are configured according to the type of analysis to be put into operation within unit 501. Individual analysis units 501 may require a certain sample volume. An individual head 522 can be used to distribute an appropriate amount of sample to an individual analysis unit 501. In this example, each head 522 corresponds to a single addressed analysis unit 501.: The mechanism of the fluid transfer device 520 can also be. used to distribute reagents from the reagent units. Different types of reagents include a conjugate solution, a washing solution and a substrate solution. In an automated system, the tier 530 on which the device 510 sits can be moved to move the device 510 in relation to the placement of the analysis units 501 and head 522 and in accordance with the steps necessary to consummate an analysis as shown in the figure. Alternatively, the heads 522 and tips 501 or the fluid transfer device 520 can be moved relative to the position of the device 510.

In some embodiments, a reagent is provided in dry form and rehydrated and / or dissolved during the analysis. Dry shapes include bi-waste materials and films coated and adhered to surfaces. An FS system may comprise a carrier or coupler for moving the analysis units or points. A coupler may comprise a vacuum assembly or a set designed to press fit a protrusion of the tip of the analysis unit. For example, means for moving the tips can be moved in a manner similar to the heads of the fluid transmission device. The device also be moved on a tier according to the position of the coupler or carrier.

In one embodiment, an instrument for moving the tips is the same as the instrument for moving a sample volume, such as a device; of fluid transfer as described herein. "For example, a sample collection tip can be adjusted over a pipette head according to the protrusion on the pickup tip.The pickup tip can then be used to distribute liquid throughout the device and system.After the liquid has been distributed, the collection tip can be discarded and the pipette head can be adjusted on an analysis unit according to the protrusion in the analysis unit. The unit of analysis can then be moved from the reagent unit to the reagent unit and the reagents can be reactive to the unit of analysis according to the suction-type or pipette-type action provided by the pipettor head. it can also be mixed with a collection tip, analysis unit or reagent unit by means of a syringe-type aspiration reaction.

A FS system may comprise a heating block for heating the analysis or analysis unit and / or for controlling the temperature of the analysis. Heat can be used in the incubation step of an analysis reaction to promote the reaction and shorten the duration necessary for the incubation step. A system may comprise a heating block configured to receive a unit of analysis. The heating block may be configured to receive a number of analysis units of a device as described herein. For example, if 8 analyzes are to be carried out on a device, the heating block can be configured to receive 8 analysis units. In some embodiments, the analysis units may be moved in thermal contact with a heating block using the means for moving the analysis units. The heating can be effected by means of heating known in the art.

An exemplary FS system 600 as described herein is shown in Figure 11. The system '600 comprises a translation tier 630 on which a 610 device (or cartridge in this example) is placed either manually or automatically or a combination of both. The system 600 also comprises heating block 640 which may be aligned with the analysis units 611"of the device 610. As shown in figure 11 the device 610 comprises a series of 8 analysis units 611 and multiple units of corresponding reagent 612 and the heating block 640 also comprises an area 641 so that at least 8 units are heated simultaneously, Each of the heating areas 641 can provide the same temperature to each individual analysis unit 611 according to the type of analysis which is carried out or the type of analyte that is detected: The system 611 also comprises a conductor (such as a photomultiplier tube) 650 for detecting a signal of a 611 analysis unit representative of the analysis direction in a Significant sample.

In one embodiment, a sensor is provided to locate the analysis unit in relation to the detector when an analysis is detected.

In one embodiment, the reader is a reader assembly that houses a detection assembly for detecting a signal produced by at least one analysis in the device. The detection assembly may be above the device or in a different orientation relative to the device based for example on the type of analysis that is performed and the detection mechanism that is used. The detection set can be moved in communication with the analysis unit or the analysis unit can be moved in communication with the detection set.

In many instances, an optical detector is provided and used as the detection device. Non-limiting examples include a photodiode, photomultiplier tube (pmt), photon counting detector, avalanche photodiode or coupled charge device (tcd). In some embodiments, a terminal diode may be used. In some embodiments, a terminal diode may be used. In some embodiments a diode, terminal can be coupled to an amplifier to create a detection device with sensitivity comparable to a pmt. Some assays can generate luminescence as described herein. In some embodiments, chemiluminescence is detected. In some embodiments, chemiluminescence is detected. In some embodiments, a detection assembly could include a plurality of fiber optic cables connected as an ace to a ccb detector or to a pmt array. The fiber optic ace could be constructed of discrete fibers or many small fibers fused together to form a solid beam. Such solid beams are commercially available and are easily interconnected to CCD detectors.

A detector may also comprise a light source, such as a light emitting diode (LED) or bulb. The light source can illuminate an analysis in order to detect the results, for example, the analysis can be a fluorescence analysis or an absorption analysis as they are commonly used with nucleic acid analysis. The detector may also comprise the optical device for feeding the light source to the analysis, such as a lens or optical fiber.

In some embodiments, the detection system may comprise non-optical sensors or sensors for detecting a particular parameter of a subject. Such sensors may include temperature, conductivity, potentiometric signals and anterometric signals, for components that are oxidized or reduced for example copying formula, copying formula or oxidizable / reducible organic compounds.

A device and / or system can after the manufacturing, be shipped to the end user, jointly or individually. The device or system of invention can be packaged with a user manual or instructions for use. In one embodiment, the system of invention is generic to the types of analyzes carried out in different devices. Because the device components can be modular, the user may only need a system and a variety of devices or analysis unit or reagent units to perform a multitude of analyzes in a point of care environment. In this context, a system can be used repeatedly with multiple devices and it may be necessary to have sensors in both the device and the system to detect such changes during packaging, for example. During packaging, changes in pressure or temperature can impact the performance of a number of components of the present system - and as such, a detector located in either one of the device or system can relieve these changes for example to the external device, in such a way that adjustments can be made during calibration or during data processing in the external device. For example, if the temperature of a fluid device is changed to a certain level during packaging, a sensor located in the device could detect this change and transport this information to the system when the device is inserted into the system by the user. There may be an additional detection device in the system to carry out these tasks or such a device may be incorporated into another component of the system. In some modalities, the information can be transmitted to either one of the system or external device. As such, the OS component of the invention or a personal computer in a local installation. The transmission may comprise wired and / or wireless connections. Also, a sensor in the system can detect similar changes. In some embodiments, it may be desirable to have a sensor in the packaging as well, either in place of the components of the system or in addition thereto. For example, adverse conditions that would revert to an invalid test cartridge or system that can be detected may include exposure to a temperature higher than the maximum tolerable or cartridge intimacy gap such as moisture penetration.

In one embodiment, the system comprises a communication set capable of transmitting and receiving information wirelessly from an external device, for example, the OS component of the present invention. Such wireless communication can use, without limitation, Wifi, Bluetooth, Zigbee, satellite, cellular or RTM technology. Various communication methods can be used, such as a wired dial-up connection with a modem with a modem, a direct link such as an IT, ISDN or cable line. In some embodiments, a wireless connection is established using exemplary wireless networks such as cellular, satellite or pager networks, GPRS or a local data transport system such as Ethernet or token ring in a local area network. In some modalities, the information is encrypted before it is transmitted. In some embodiments, the communication set may contain a wireless infrared communication component to send and receive information. The system can include integrated graphics cards to facilitate the display of information.

In some embodiments, the communication set may have a memory or storage device, for example localized RAM, in which the collected information may be stored. A storage device may be required if the information can not be transmitted at a given time due, for example, to a temporary inability to connect wirelessly to a network. The information may be associated with the identifier of the device in the storage device. In some embodiments, the communication set may retry sending the stored information after a certain amount of time.

In some embodiments, an external device, for example, the OS portal component of the invention, communicates with the communication set within the reader assembly. An external device can be communicated wired or physically with the FS system, but it can also communicate with a third party, including without limitation an individual, medical personnel, physicians, laboratory personnel or others in the health care industry. * An exemplary method and system is demonstrated in Figure 12. In the example of Figure 12, a patient provides a blood sample to a device as described herein and then the device is inserted into a reader, wherein the device is inserted into a reader. Reader can be a desktop system able to read an analyte in the blood sample. The reader may be a system as described herein. The reader may be a bank or desktop / desktop system and may be able to read a plurality of different devices as described herein. The reader or system is able to carry out a chemical reaction and detect or read the results of the chemical reaction. In the example of Figure 12, a reader is automated according to a protocol sent, from an external device (for example, a server, comprising a user interface). A reader can also send the results of the chemical reaction detection to the server and user interface. In an exemplary system, the user (for example, medical personnel such as a physician or researcher) can observe and analyze the results as well as decide or develop the protocol used to automate the system. The results can also be stored locally (in the reader) or in the server system. The server can also host patient registration, a patient diary and patient population databases.

Figure 13 illustrates the process flow of constructing a system for determining the medical condition of an individual according to a modality of the HS system described herein. The patient enters personal data and / or measurements of a device, reader and / or system as described herein in a database as it may be present on a server, for example, the OS component. The FS system can be configured to display personal data on a screen of the patient station. In some modalities, the screen of the FS station is interactive and the individual can modify the entered data. The OS database contains data from other individuals that are monitored by the Health Shield. The HS database may also include data from other individuals historically collected from public or private institutions. In some modalities, the data of other individuals are internal data of a clinical study.

Figure 13 also illustrates the collection data data flow of the reader that includes the data of the subject to a server that is connected in a public network. The server can manipulate the data or can only provide the data to a user station. Patient data can also be entered into the server separately from data pertaining to a medical condition that is stored in a database. Figure 13 also demonstrates a user station display and the flow of information to medical personnel or a user. For example, using the exemplary process flow of Figure 13, a patient at home can introduce a body fluid sample to a cartridge of the invention as described herein and place it in a system or reader as described herein. . The patient can observe the data from the system on a screen of the patient station and / or modify or introduce new data to the process flow. The patient data can then travel in a public network, such as the internet, for example, in an encrypted format, to a server comprising a network interface and a processor, where the server is located in a central computing hub or in a clinical testing center. The server can use medical condition data to manipulate and understand user data and then send the results in a public network as described to a user station. The user station may be in a medical office or laboratory and have a user station display to show the results of the analysis and manipulation of patient data to medical personnel. In this example, the medical staff can receive results and analyzes of a patient sample from < a test that the patient administered at an alternate site such as the patient's home. Other embodiments and examples of systems and system components are described herein.

The OS component of the HS system can store protocols to be executed in an FS system.

The protocol can be transmitted to the communication set of an FS system after the OS has received an identifier indicating which device has been inserted into the FS system. In some embodiments, a protocol may be dependent on a device identifier. In some embodiments, the OS component stores more than one protocol for each field device. In other modalities, the patient information in the external device includes more than one protocol. In some instances,. The OS component stores mathematical algorithms to process a photon count sent from a communication set and in some modalities to calculate the analyte concentration in a body fluid sample.

Having the FS components and system OS integrated into a network connection provides a variety of advantages. For example, the information can be transmitted from the operating system back not only to the FS reader set, but to other parts or other external devices, for example without limitation, a PDA or cell phone. -Tal communication can be carried out via a wireless network as revealed in the present. In some embodiments a calculated analyte concentration or other patient information may be sent to, for example but not limited to, medical personnel or the patient. In a non-limiting example, a quarantine notification can be sent to both the infected individual and medical personnel who can put quarantine in place.

In some modalities, the data generated with the use of the present devices and systems can be used to carry out a trend analysis in the concentration of an analyte of interest.

Another advantage as described herein is that the analysis results can be reported substantially immediately to any third party who may benefit from obtaining the results. For example, once the analyte concentration is determined in the operating system component, it can be transmitted to a patient or medical staff that may need to take additional action. This could include 'identification of an index case. The communication stage to a third party can be carried out wirelessly as described herein and when transmitting the data to a portable device of the third party, the third party can be notified of the analysis results at virtually any time and in any place. Thus, in a time sensitive scenario, the patient can be contacted immediately anywhere if urgent medical action may be required.

By detecting a device based on an identifier associated with a fluid device after it is inserted into the FS system, the system allows the specific protocols of the fluid device to be downloaded from an external device, for example, the OS component. and put into operation. In some embodiments, the OS component may store a plurality of protocols associated with the system or associated with a particular individual or group of individuals. For example, when the identifier is transmitted to the OS component, the programming elements in the OS component, such as a database, can use the identifier to identify protocols stored in the database associated with the identifier. If only one protocol is associated with the identifier, for example, the database can select the protocol and programming elements in the external device can then transmit the protocol to the communication set of the system. The ability to use protocols associated specifically with a device allows any component of a device of the invention to be used with a single system and thus virtually any analyte of interest can be detected with a single system.

In some modalities, multiple protocols may be associated with a single identifier. For example, if it is beneficial to detect an analyte once a week from the same individual and another analyte twice a week, the protocols in the external device associated with the identifier can also be associated with a different day of the week, in such a way that when the 'identifier is detected, the programming elements in the external device can select a specific protocol that is associated with the day of the week. Such optimized tests can reduce the cost of the HS system by only performing analyzes according to an optimized schedule.

In some embodiments, an individual is provided with a plurality of devices to be used to detect a variety of analytes. The individual can use for example different devices on different days of the week. In some embodiments, the programming elements in the operating system that associate the identifier with a protocol may include a process for comparing the current day with the day when the device will be used based on a clinical test for example. If, for example, the two days of the week are not identical, the operating system can wirelessly notify the subject using any of the methods described herein or known in the art to notify them that an incorrect device is in the system and also of the correct device to use that day. This example is only illustrative and can easily be extended to, for example, notifying a subject that a device is not being used at the correct time of day.; The system can also use a network method to determine the medical condition of a subject. A system of communicating information may or may not include a reader to read data of the subject. For example, if biomarker datds are acquired by a microfluidic point of care device, the values assigned to different individual biomarkers may be read by the device itself or a separate device. Another example of a reader would be a bar code system to scan on subject data that has been entered into an electronic medical record or a doctor's chart. An additional example of a reader would consist of an electronic patient record database from which subject data can be obtained directly via the communication network. In this way, the effectiveness of particular drugs can be determined in real time, thereby helping to determine if a different mitigation strategy should be put in place. (b) Field System Methods The FS devices described herein provide an effective means for the real-time detection of analytes present in the body fluid of a subject. Thus, in one embodiment, the present invention makes use of a method for detecting an analyte in a body fluid sample, comprising providing a blood sample to an FS device, allowing the sample to react within at least one unit. of analyzing the device and detecting the detectable signal generated from the analyte in the blood sample.

Figure 5 demonstrates an exemplary embodiment of an FS device comprising at least one analysis unit and at least one reagent unit. The analysis units (eg, designated as sample tips or calibrator tips in Figure 5) may contain a capture surface and the reagent units may contain items such as conjugates, washes and substrates. The device shown in Figure 5 also comprises a whole blood sample collection tip, a plasma sample collection tip, a blood entry cavity, a bead cavity or a plasma separation cavity, a bearing no tip contact or immunoabsorption, a dilution cavity, a diluted plasma sample cavity or plasma diluent cavity, waste tip disposal areas.

In one embodiment, one method comprises performing an enzyme-linked immunosorbent assay (ELISA). In one example, a sample is provided to the sample collection unit of a device as described herein. The device is then inserted into a reader system, wherein the reader system detects the type of cartridge or device that is inserted. The reader system can then communicate with an external device, for example the OS component of the HS system, to receive a set of instructions or protocol that allow the reader system to carry out the desired analysis or analysis of the cartridge. The protocol can be sent to the programmable processor of a fluid transfer device of the reader system. In one example, the fluid transfer device engages a sample tip of the cartridge and collects a certain volume of the sample from the sample collection unit and carries it to a pretreatment unit where the blood cells Blood reds are removed. The plasma of the sample can then be aspirated to a plasma tip or any analysis tip using the device fluid transfer device according to the protocol. The tip containing the plasma can then collect a diluent to dilute the sample as'! it is necessary for the analyzes to be executed. Many different dilutions can be carried out by using serial dilutions of the sample. For example, each analysis tip or analysis unit may contain a sample of a different dilution. After the sample is aspirated into a unit of analysis by the fluid transfer device, the analysis unit can then be incubated with the sample to allow any target analyte present to be attached to the capture surface. Incubations as described in this example may be in the system or room temperature for any period of time, for example 10 minutes or may be in a heating device of the systems described herein. The analysis unit can be coupled with a reagent unit addressed with a reagent corresponding to the analysis to be executed in each individual analysis unit that has a capture surface for that analysis. In this example, the first reagent is an ELISA detector solution, for example, which comprises a detector antibody such as a labeled anti-protein antibody different from that of the capture surface. The detector solution is then aspirated from the analysis unit and then a washing solution can be drawn into the analysis unit to remove any excess detector solution. Multiple stages of washing can be used. The final reagent to be added is an enzyme substrate that causes the bound detector solution to be chemiluminescent. In some modalities, the results of the analysis are read by a system detector while the tip still contains the analysis product. In other embodiments, the enzymatic substrate is ejected from the analysis unit and the results 1 of the analysis are read by a system detector. At each stage as described, incubations may be presented as necessary as described herein. In this example, the entire process after putting the cartridge into the system is automated and carried out by a protocol or set of instructions to the programmable system.

An exemplary method proceeds with the administration of a blood sample to the blood entry cavity. The sample can then be collected by a collection tip and inserted into the plasma separation cavity. Alternatively, the blood can be directly deposited in a cavity containing a blood separator. For example, plasma separation can be carried out by a variety of methods as described herein. In this example, plasma separation proceeds using magnetizable beads and antibodies to remove non-plasma blood components. The plasma can then be transported by a plasma collection tip so as not to contaminate the sample with the whole blood collection tip. In this example, the plasma collection tip can capture a predetermined amount of diluent and dilute the plasma sample. The diluted plasma sample is then distributed to the analysis units (sample tips) to link to a capture surface. The units of analysis can be incubated to allow a capture reaction to take place. The unit of analysis can then be used to collect a conjugate to link to the reaction in the unit of analysis. The conjugate may comprise an entity that allows the detection of a. analyte of interest by a detector, such as an optical detector. Once the conjugate has been added to the analysis unit, the reaction can be incubated. In an exemplary method using the exemplary device of Figure 5, a reagent unit containing a wash for the conjugate is then accessed by the analysis unit (sample tip) to remove any excess conjugate that may interfere with the detection of analyte. After washing the conjugate in excess, a substrate can be added to the analysis unit for detection. In addition, in the example given in Figure 5 and this method, a calibrator tip analysis unit can be used to carry out all the methods described in this paragraph except the collection and distribution of the sample. The detection and measurements using the calibrator tip analysis unit can be used to calibrate the detection and measurements of the analyte in the sample. Other processes and methods similar to those used in this example are described later herein.

Any suspect bodily fluids: of containing an analyte of interest can be used in conjunction with the system or devices of the invention. For example, the entry cavity or sample collection unit in the example of Figure 5 can collect to contain any type of commonly used body fluids including, but not limited to, blood, serum, saliva, urine, gastric fluid and digestive, tears, feces, semen, vaginal fluid, interstitial fluids derived from tumorous tissue fluids extracted from tissue samples and cerebrospinal fluid. In one embodiment, the body fluid is blood and can be obtained by a finger prick. In one embodiment, the body fluid sample is a sample of blood plasma. In another embodiment, the body fluid sample is an unmodified blood sample.

A body fluid can be extracted from a patient and distributed to the device in a variety of ways including, but not limited to, lancet, injection or pipetting. In one embodiment, a lancet pierces the skin and delivers the sample to the device using for example gravity, capillary action, aspiration or vacuum force. The lancet may be on board the device or be part of a reader assembly or an autonomous component. Where needed, the lancet can be activated by a variety of mechanical, electrical, electromechanical activation mechanisms or any other known activation mechanism or any combination of such methods. In another embodiment where no active mechanism is required, the individual can simply provide the body fluid to the device, as might occur, for example, with a saliva sample. The collected fluid can be placed in a collection cavity or unit of the device. In some modalities, there is a lancet activated by the user and capillary of sample collection within the device.

The volume of body fluid to be used with the method or device described herein is generally less than about 500 microliters, may also be between about 1 to 100 microliters. Where desired, a sample of 1 to 50 microliters, 1 to 40 microliters, 1 to 30 microliters, 1 to 10 microliters or even 1 to 3 microliters can be used to detect an analyte using the fluid device present. In one embodiment, the sample is 20 microliters. A slight excess of sample can be collected with respect to that required for the analysis, for example, 1%, 2%, 3%, 4%, 5%, 6%, 7%, 8%, 9%, 10%, 12%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, 50%, 55%, 60%, 65%, 70%, 75%, 80%, 85%, 95% or 100% extra. In some modalities, more than 100% extra sample volume is collected. For example, when the sample volume required for the analysis is, for example, 15 uL, the system can use a volume in the range of 16-50 uL.

In one embodiment, the volume of body fluid used to detect an analyte in the field is a drop of fluid. For example, a drop of blood from a chopped finger can provide the body fluid sample to be analyzed according to the invention.

In some embodiments, body fluids are used directly to detect analytes present in the body fluid without further processing. Where desired, however, bodily fluids can be pre-treated before performing the analysis with a device. The choice of pre-treatments will depend on the type of body fluid used and / or the nature of the analyte under investigation. For example, where the analyte is present at a low level in a body fluid sample, the sample can be concentrated via any conventional means to enrich the analyte. Methods of concentration of an analyte include but are not limited to drying, evaporation, centrifugation, sedimentation, precipitation and amplification. Where the analyte is a nucleic acid, it can be extracted using various lithic enzymes or chemical solutions or using nucleic acid binding resins following the attached instructions provided by the manufacturers. For blood or plasma samples, the sample can be mixed with an anticoagulant such as EDTA or heparin. These agents can conventionally be added in dry form. Where the analyte is a molecule present on or within a cell, the extraction can be effected using lysis agents in which, but not limited to, anticoagulants such as EDTA or heparin, a denaturing detergent such as SDS or non-detergent. denaturing such as Thesit®, sodium deoxycholate, triton X-100 and tween-20.

In one embodiment, the user collects a sample of body fluid with a syringe. The sample can enter the syringe through a capillary tube. In a method that measures an analyte in a blood sample, the subject makes a finger prick and touches the outer end of the glass capillary to the blood, in such a way that the blood is extracted by capillary action and fills the capillary with a volume. In some instances, the sample volume is known. In some embodiments, the sample volume is in the range of about 5-20 microliters or other volume ranges as described herein.

In another embodiment, a method and system for obtaining a plasma sample substantially free of red blood cells from a blood sample is provided. When an analysis is performed, the analytes are often contained in the blood plasma and the red blood cells can interfere with a reaction.

Frequently, when measuring a blood sample, the analytes of interest are in the serum or plasma. For clinical purposes, the final reported concentration of multiple blood tests. it frequently needs to be related to the concentration of serum in the blood or plasma in the blood in a diluted sample. In many cases, serum in the blood or plasma in the blood is the test medium of choice in the laboratory. Two operations may be necessary before performing an analysis, dilution and removal of red blood cells. Blood samples vary significantly in the proportion of the volume of sample occupied by the red blood cells (the hematocrit varying from approximately 20-60%). In addition, in a point-of-care environment when the analysis systems are put into operation by non-expert personnel, for example, a device deployed in the home of an individual that is monitored by the Health Shield, the volume of sample obtained It can not be the one that is destined. If a change in volume is not recognized, it can lead to an error in the analyte concentrations reported.

In a related but separate embodiment, the present invention uses a method for recovering plasma from a blood sample comprising mixing the blood sample in the presence of magnetizable particles in a sample collection unit, wherein the particles I magnetizable comprise an antibody capture surface for binding to the plasma-free portions of the blood sample and applying a magnetic field over a plasma collection area to the mixed blood sample to effect suspension of the plasma-free portions. of the blood sample above the plasma collection area, thereby recovering the plasma of a blood sample.

In order to process blood samples, the device or system of the invention may include a magnetic reagent or object that binds to red blood cells and allows the magnetic removal of red blood cells from the plasma. The reagent may be provided in lyophilized form, but may also be present as a liquid dispersion. A reagent consisting of magnetizable particles (e.g., about 1 miera in size) can be coated with an antibody to an antigen of red blood cells or some adapter molecule. In some embodiments, the reagent also contains antibodies without binding to the surface antigens of red blood cells, which may be unlabelled or labeled with an adapter portion (such as biotin, digoxigenin or fluorescein). In a modality that analyzes a blood sample, the red blood cells in a diluted sample co-agglutinate with the magnetizable particles aided by a solution-phase antibody. Alternatively, a lectin that recognizes a carbohydrate on the surface of red blood cells may be used as a co-agglutination agent. Sometimes combinations of red blood cell agglutination agents are used. Alternatively, the device of the invention may comprise a blood filter, such as a fiberglass bearing, to aid in the separation of red blood cells from a sample.

When the blood is mixed with a magnetic reagent, a co-agglutination can occur in which many, if not all, of the red blood cells form a binder mixed with the magnetizable particles. The process of dissolving and mixing reagent is driven by repeated aspiration using a tip or collection tip of the invention or a pipette-like tip. After the magnetizable mass has formed, the mass can be separated from the blood plasma by using a magnet to hold the mass in place as the plasma is allowed to come out of the tip. In one embodiment, the plasma leaves the tip by gravity in a vertical orientation, while the magnet keeps the mass in place. In another embodiment, the plasma exits the tip by vacuum or pressure means, while the mass is maintained within the tip. The plasma can be deposited in a channel, another collection point or unit of analysis as described herein.

An example of a plasma separation method of the invention is shown in Figures 14A to 14E. In Figure 14A, a sample of whole blood 901 aspirated has been to a sample tip 910 as described herein, for example, in the amount of approximately 20 microliters. The whole blood sample 901 is then deposited in a separation cavity 920 (e.g., a cavity containing magnetic beads or particle) of an exemplary device. Figure 14B illustrates a method of suspending and mixing a magnetic reagent in the whole blood sample 902 in a separation cavity (e.g., magnetic beads particles and free binding molecules). Figure 14C demonstrates a 10 microliter suspension 930 which can be used to prevent the loss of tip 910. The sample of whole blood and mixed magnetic reagent 902 are incubated for several seconds (eg, 60 to 180 seconds) to allow an agglutination reaction occurs.

Figure 14D shows the application of a 940 magnetic field to the mixture of. whole blood and magnetic reagent cells 902. The magnetic field 940 'may be applied by a magnetic collar 942 which is incorporated with a system or with any magnetic means known in the art. The magnetic field 940 attracts any particles that have adhered to the magnetic reagent. In this manner, plasma 903, which does not adhere to the magnetic reagent, can be separated from the plasma-free portions of a whole blood sample.

Figure 14E demonstrates a method for distributing a blood plasma sample 903, as separated by the magnetic reagent described herein, to a cavity or device unit 950 as described herein. The blood plasma sample 903 can also be distributed to a collection tip or unit of analysis, as well as any other kind of analytical device as is obvious to one skilled in the art. In Figure 14E, the magnetic field 940 is shown moving with the tip 910 distributing the blood plasma sample 903. In this example, 5 to 8 microliters of plasma have been removed from a 20 microliter whole blood sample. 1 to 99% of a whole blood sample can be separated in plasma using a method described herein. In one embodiment, 25 to 60% of the volume of the whole blood sample is plasma that can be separated.

Other exemplary steps of a method as described herein may be accomplished. In order to move the blood plasma sample to another cavity or unit, a capillary plasma collection tip (which can be operated by a robotic system or any other system of the invention) collects the blood plasma sample by capillary force and aspiration. Another step may comprise distributing the plasma sample in a diluent, and the sample may then be diluted by the diluent. The diluted blood plasma sample can then be collected by the collection tip in a predetermined volume. The sample of diluted blood plasma can then be mixed and distributed to a cavity or unit of a device to be distributed to one or a plurality of analysis units of a device of the invention. The sample can also be distributed to any other type of device, such as a microtiter plate, as would be obvious to one skilled in the art.

'The exemplary process shown in Figures 14A a 14E can be used with other devices and systems, such as any of the FS devices described herein. For example, a fluid transfer tip may contain the agglutinated mass and the plasma may be deposited in a microtiter plate. Other devices and systems as would be obvious to those skilled in the art could be used to execute the exemplary plasma separation as disclosed herein.

The body fluid sample can also be diluted in a variety of other ways, such as by using a sample collection device suitable for dilution. The housing of the sample collection device may comprise a tube. In the tube, two movable seals can contain a volume of a diluent. In a preferable embodiment, the volume of the diluent is predetermined, for example, in the range of about 50 microliters to 1 milliliter, preferably in the range of about 100 microliters to 500 microliters.

In one embodiment, the FS devices of the invention are used in a method for automated detection of a plurality of analytes in a body fluid sample comprising: providing the body fluid sample to a fluid device, wherein the device fluid comprises: a sample collection unit configured to contain the body fluid sample; an array of analysis units, wherein an individual analysis unit of said array of analysis units is configured to execute a chemical reaction · which produces a signal indicating an individual analyte of a plurality of analytes that are detected, and an array of reagent units, wherein a single reagent unit of said array of reagent units contains f a reagent. The method may also comprise coupling the individual analysis unit using a fluid transfer device. Continuing with the method, the body fluid sample can be transferred from the sample collection unit to the individual analysis unit using the fluid transfer device and the reagent from the individual reagent unit can be transferred to the unit. individual analysis, thereby reacting the reagent with the body fluid sample to produce the indicia signal of the individual analyte of the plurality of analytes that are detected. In some embodiments, the fluid transfer device comprises a plurality of heads, wherein an individual head of the plurality of heads is configured to be coupled to the individual analysis unit, and wherein the fluid transfer device comprises a programmable processor configured to direct the fluid transfer from the body fluid sample of the sample collection unit and the reagent from the individual reagent unit to the individual analysis unit.

In some instances, instructions are provided to the programmable processor, for example, by a user, an individual, or the manufacturer. The instructions may be provided from an external device, such as a personal electronic device or, preferably, from the OS component of the Health shielding system. The instructions can direct the stage of transferring the body fluid sample to the individual analysis unit. For example, the transfer step of the body fluid sample can effect a degree of dilution of the body fluid sample in the individual analysis unit to bring the signal indicating the individual analyte of the plurality of analytes that are detected inside. of a detectable interval. In some examples, the degree of dilution of the body fluid sample brings the signal indicative of at least two individual analytes within a detectable range as described herein.

Pattern recognition techniques can be used to determine whether the detection of an analyte or a plurality of analytes by a method as described herein is within or outside a certain range. For example, detectable signals outside the reportable interval can be. rejected. At a certain interval it can be established during the calibration of a reagent fluid device and analysis units. For example, the interval is set when a device is assembled just in time.

In some instances, if the detectable signal of an analyte as detected with a low dilution factor or the degree of dilution exceeds a higher dilution factor, the result of lower dilution can be identified as insufficient to calculate a quantitative result. In most instances, the concentrations of an analyte in a sample as they are derived from signals from samples with different degrees of dilution become lower as the degree of dilution becomes higher. If this happens, a result of the analysis can be verified. The FS devices described herein provide the flexibility of quality control rules such as those described that many POC devices can not offer. The FS devices described provide many of the quality control elements, as you would expect in a laboratory installation.

In one embodiment, a sample is diluted in a proportion that is satisfactory both for high sensitivity and for low sensitivity analysis. For example, a dilution ratio of sample to diluent may be in the range of approximately 1: 10,000-1: 1. The device may allow a sample to be diluted in separate sites or extensions. The device may also allow the sample to be subjected to serial dilutions. The combination of the use of serial dilution with the wide dynamic range of luminescence detection with a PMT provides quantification of analytes in a range of approximately one billion times. For example, for protein biomarkers, the range can be from about 1 microgram / ml to 1000 microgram / ml.

In embodiments, a sample containing an analyte for detection can be moved from a first site to a second site by aspiration-type action, syringe or pipette. The sample can be extracted to the reaction tip by capillary action or reduced atmospheric pressure. In some embodiments, the sample is moved to many sites, including an array of analysis units of a device of the invention and different cavities in the housing of a device of the invention. The process of moving the sample can be automated by a system of "the invention, as described herein.

The analysis units and / or collection points containing the sample can also be moved from a first site to a second site. The process of moving an analysis unit or a collection point can be automated and carried out by a user-defined protocol.

In one embodiment, the analysis units are moved to collect reagent from a reagent unit of the invention. In many modalities, the movement of a unit of analysis is automated. Suction type action, the syringe, pipette can be used to collect the reagent from a reagent unit to a unit of analysis.

Once a sample has been added to an analysis unit comprising a capture surface, the entire unit can be incubated for a period of time to allow a reaction between the sample and the capture surface of the analysis unit. The amount of time necessary to incubate the reaction is often dependent on the type of analysis performed. The process can be automated by a system of invention. In one embodiment, the incubation time is between 30 seconds and 60 minutes. In another modality, the incubation time is 10 minutes.

A unit of analysis can also be incubated at an elevated temperature. In one embodiment, the analysis unit is incubated at a temperature in the range of about 20 to 70 degrees Celsius. The analysis unit can be inserted into a heating block to raise the temperature of the analysis unit and / or the content of the analysis unit.

In one embodiment of an FS method of the invention, a conjugate is added to the analysis unit after a sample has been added to the unit. The conjugate may contain a molecule for labeling an analyte captured by a capture surface in the analysis unit. Examples of conjugates and capture surface are described hereinafter. The conjugate can be a reagent contained within a reagent unit. The conjugate can be distributed to the unit of analysis by means of suction-type action, syringe or pipette. Once a conjugate has been distributed to a unit of analysis, the unit of analysis can be incubated to allow the conjugate to react with an analyte within the unit of analysis. The incubation time can be determined by the type of analysis or the analyte to be detected. The incubation temperature can be any temperature appropriate for the reaction.

In another embodiment, a method of calibrating a device for the automatic detection of an analyte in a body fluid sample is used with the FS device of the invention. The device may comprise an array of addressable analysis units configured to perform a chemical reaction that produces a detectable signal indicating the presence or absence of the analyte, and an array of addressable reagent units, each of which is addressed to correspond to one or more addressable analysis units in the device, such that the individual reagent units are calibrated with reference to the corresponding analysis unit (s) incorporated in a complete analysis device. The final multiplexed device can then be assembled using the calibrated components, making the device, and a method and system using the device, modular components. In some embodiments, the calibration for multiplexed analyzes is carried out as before, using all analyzes simultaneously in a multiplexed analysis device.

Calibration may be pre-established by measuring the performance of assay reagents, such as conjugates, before the analysis units and reagent unit are assembled in a device of the invention. Calibration information and algorithms can be stored in a server wirelessly linked to the analysis system. The calibration can be carried out in advance or retrospectively by analysis carried out in replica systems in a separate site or by using information obtained when the analysis system is used.

In one aspect, a control material can be used in a device or system to measure or verify the extent of dilution of a body fluid sample. For example, another issue of solid phase base analyzes such as ELISA is that an analysis uses a solid phase reagent that is difficult to control in quality without destroying its function. The systems and methods herein provide methods for determining the dilution obtained in a POC system using a disposable device 1 with automated mixing and / or dilution.

In one modality, a method provides retrospective analysis, 'for example, by using the OS component to analyze the data in real time before reporting results. For example, an analysis can be performed and a witness analysis can be executed in parallel to the analysis. The control analysis provides a measurement of. an expected dilution of the sample. In some examples, the control analysis can verify the dilution of the sample and, thus, dilution of the sample for the analysis or plurality of analyzes performed within the system can be considered accurate.

A method for measuring a volume of a liquid sample may comprise: reacting a known amount of a control analyte in a liquid sample with a reagent to produce a detectable signal indicating the control analyte, and comparing the intensity of the detectable signal with an intensity expected from said detectable signal, wherein the expected intensity of the signal is indicative of an expected volume of the liquid sample, and wherein said comparison provides a measurement of the liquid sample volume that is measured. In many instances, the control analyte is not present in the liquid sample in a detectable amount.

In one embodiment, the method may further comprise verifying the volume of the liquid sample when the measurement of the volume of the sample is within approximately 50% of the expected volume of the liquid sample.

For example, a method using an FS device described herein may further comprise: reacting a sample of body fluid containing an objective analyte with a reagent to produce a detectable signal indicative of the target analyte, and measuring the amount of the target analyte in the sample of body fluid using the intensity of the detectable signal indicating the target analyte and the measurement of the volume of the liquid sample. The liquid sample and the body fluid sample can be the same sample. In some embodiments, the control analyte does not react with the target analyte in the body fluid sample, thereby providing no interaction by detection of the target analyte.

In some instances, the liquid sample (to be used - as a control) and the body fluid sample; they are different liquid samples that contain the analyte of interest. For example, a control liquid, such as a control solution containing a known control analyte level. This type of witness verifies that the analysis chemistry is operating properly.

A control analyte used to verify the correct dilution of a sample may be, without limitation, fluorescein-labeled albumin, fluorescein-labeled IgG, anti-fluorescein, anti-digoxigenin, digoxigenin-labeled albumin, digoxigenin-labeled IgG, biotinylated proteins, IgG not -human Other exemplary control analytes can? be obvious to the experienced in the art. In one embodiment, the control analyte is not present in a sample of human body fluid. In some embodiments, the control analyte is added as a liquid or in dry form to the sample.

In a POC system as described herein configured to detect a plurality of analytes within a sample, the system may have capabilities to dilute and mix liquids. In many instances, an automated system or user can use a control analysis to measure the dilution actually obtained and take into account that dilution in the calibration of the system. For example, a control analyte can never be found in the sample of interest and dried to a reagent unit. The amount of the dry control analyte can be known and mixed with 1; a sample in the reagent unit. The analyte concentration can be measured to indicate the sample volume and any dilution made on the sample.

Examples of control analytes for an immunoassay include, but are not limited to: fluorescein labeled protein, biotinylated protein, fluorescein-labeled, Alexa-labeled, rhodamine-labeled immunoglobuyin, Tjexas Red-labeled. For example, labeling can be obtained by having at least two haptens bound per protein molecule. In some embodiments, 1-20 haptens are linked per protein molecule. In a further embodiment, '4-10 haptens are linked per protein molecule. Many proteins have large numbers of free amino groups to which haptens can be attached. In many instances, modified hapten proteins are stable and soluble. Also, haptens such as Fluorescein and Texas Red are sufficiently large and rigid that antibodies can be made with high affinity (for example, a haptens is large enough to fill the antibody binding site). In some embodiments, haptens can be attached to proteins using reagents, such as fluorescein isionosinate, and NHS fluorescein carboxylic acid ester to create control analytes which the part recognized by the assay system is hapten.

In some embodiments, the method uses dry control analyte. In some examples, the dry control analyte prevents dilution of the sample and can make the control analyte more stable. The dry control analyte can be formulated in such a way that it dissolves rapidly and / or completely on exposure to a liquid sample. In some embodiments, a control analyte may be an analyte for which antibodies with high affinity. In some instances, an analyte. The control can be an analyte that does not cross-react with any endogenous mutant component. Additionally, for example, the analyte can; be not expensive and / or easy to manufacture. In some embodiments, the control analyte is stable over the life of the device or system described herein. Exemplary carriers used to create analytes with haptens covalently linked include proteins such as, but not limited to: albumin, IgG and casein. Exemplary polymeric carriers used to create the new analytes with haptens covalently linked include but are not limited to: dextran, polyvinylpyrrolidone. Exemplary excipients used to formulate and stabilize control analytes include but are not limited to: sucrose, salts and pH-regulating solutions (such as sodium phosphate and tris-chloride).

A control analyte and method as described herein can be used in a variety of ways including the examples described herein.; For example, a method can measure the volume of a sample; In some embodiments, the method measures the dilution or a dilution factor or a degree of dilution of a sample. In some instances, the method provides a concentration of the control analyte in a sample. In a system or device disclosed herein to detect a plurality of analytes, measurements of a method herein using a control analyte can be used to verify or describe measurements of target analytes. For example, a fluid transfer device with multiple heads can be used to distribute liquid to a plurality of analysis units, including a control unit. In some instances, it can be assumed that the amount of liquid distributed to the plurality of units is the same or similar among the individual units. In some embodiments, the method described herein with a control analyte can be used to verify that the correct volume of sample has been collected or used within the device or system. In another embodiment, the method verifies that the correct volume of diluent has been provided to the sample. Also, the dilution factor or degree of dilution can also be verified. In still another embodiment, a method with a control analyte verifies that the correct volume of diluted sample has been distributed to the plurality of units.

Figure 15 demonstrates an exemplary method of a control analysis as described herein comprising a known amount of control analyte. A unit 1010 prior to mounting to a cartridge can be filled with a solution 1001 comprising a known mass of control analyte 1002. The liquid in the solution can be dried to leave control analyte 1002 in unit 1010. Unit 1010 can then be inserted into a device and transported for use. When the unit 1010 is used and receives a sample of diluent 1003, the sample 1003 can be administered in an expected volume and mixed with the dry control analyte 1002 within the unit 1010 to create a control solution 1004 with an expected concentration. The control solution 1004 can optionally be diluted. In one embodiment, the control analyte 1002 can be detected in the same manner as the target analyte in the device. The concentration of control analyte in control solution 1004 is measured. The concentration measurement can be used to calculate the volume of the aggregate sample 1003 to create the control solution 1004. In this way, the user can compare the measured volume of the sample 1003 with the expected volume of the sample 1003.

In one example, red blood cells can be removed from a blood sample. However, if some red blood cells remain or red blood cells are not removed from a blood sample, a method with a control analyte can be used to correct the effects of red blood cells on the blood sample. Because the hematocrit can vary significantly (for example, from 20-60% of the total volume of a sample), the amount of an analyte in a fixed or expected volume (v) of blood can be a function of the hematocrit (H expressed in the present as a decimal fraction). For example, the amount of analyte- with a concentration C in plasma is C * v * (l-H). Thus the amount for a sample with hematocrit 0.3 is 1.4 times that for a sample with a hematocrit 0.5. In an exemplary embodiment, undiluted blood can be delivered to the device as described herein and the red blood cells can be removed. The concentration of the control analyte in the plasma fraction can then be measured to estimate the volume of the sample plasma and determine the hematocrit.

In some embodiments, the unbound conjugate may need to be washed from a reaction site to prevent unbound conjugates from producing inaccurate detection. The limiting step of many immunoassays is the washing step. The intermediate solution of minimal transport and high sensitivity is dependent on the wash removal of the unbound conjugate. The washing step can be severely limited in a microtiter plate format due to the difficulty of removing the washing liquid from a cavity (eg, by automatic means). A device of the analysis unit can have a variety of advantages in that the way in which liquids are handled. An advantage may be an improvement in the signal to noise ratio of the analysis.

Removal of the conjugate can be difficult if the conjugates are stuck to the edges of the device analysis units if, for example, there is no excess wash solution. A wash of the conjugate can occur either by pushing the wash solution from above or by attracting the wash solution upwards and expelling the liquid similar to the load of the sample. The washing can be repeated as many times as necessary.

. When a wash buffer solution is used in an analysis, the device can store the washing buffer solution in reagent units and the analysis unit can be brought into fluid communication with the wash. In one embodiment, the washing reagent is capable of removing the unbound reagent from the analysis units by approximately 99, 99.9 or 99.999% per wash. In general, a high washing efficiency that results in a high degree of reduction of undesirable background signals is preferred. The washing efficiency is commonly defined by the signal proportion of a dacio analysis to the total amount of signal generated by an analysis without washing step and can be easily determined by routine experimentation. It may be generally preferred to increase the volume of the wash solution and incubation time but without sacrificing the signals of a given analysis. In some embodiments, washing is effected with about 50 ul to about 5000 ul of wash buffer, preferably between about 50 ul to about 500 ul of wash buffer, for about 10 to about 300. seconds .

Additionally, it may be advantageous to use several cycles of small volumes of wash solution that are separated by periods of time where wash solution is not used. This sequence allows for diffusive washing, in which the markers are diffused over time to the overall wash solution of the protected parts of the analysis unit such as the edges or surfaces where it is loosely bonded and can then be removed when the wash solution is moved from the reaction site.

In many embodiments, the last step is to distribute an enzyme substrate to detect the conjugate by optical or electrical means. Examples of substrates are described later herein.

For example, the reagent in the individual reagent unit of a device herein can be an enzyme substrate for an immunoassay. In another embodiment, the step of transferring the substrate reagent from the individual reagent unit can be repeated after the reaction at the capture site. For example, the enzyme substrate is transferred to a reaction site and incubated. After measuring the produced analysis signal, the substrate used can be removed and replaced with new substrate and the analysis signal be re-measured .. A signal indicating the individual analyte that is detected using a system as described herein both the first and second application of the substrate. The second substrate is usually the same as the original substrate. In one embodiment, the second substrate is transferred to a reaction site of a second reagent unit of a device herein. In another embodiment, the second substrate 'is transferred to a reaction site of the same reagent unit as the original substrate. The transfer of a second substrate thereby creates a second reaction to produce a second signal indicating the individual analyte. The intensity of the original signal and the second intensity of the second signal can be compared to calculate the intensity, end of the signal indicating the individual analyte and if the analysis was carried out properly.

In one embodiment, the intensities of the multiple signals can be used for quality control of the analysis. For example, if the signals differ by 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, 100% or more, the analysis results can be discarded.

In one embodiment, a method as described herein comprises re-loading the sample and / or detector-conjugate (enzyme-labeled antibody) and / or enzyme substrate and sample to rectify or confirm a test signal or use as internal witness. For example, the reuse of an analysis tip or unit as described herein may be provided to verify the function and / or to add additional sample or control materials to obtain a second signal.

In some instances, a method to re-load a substrate to an enzyme unit is. enabled by the ability of the system as described herein to automatically transfer liquid and reactive samples to the analysis units. Some analyzes do not require the system to feed a result immediately or on a schedule, therefore, a control method as described offers the opportunity to possibly improve the reliability of the results. A response observed next to iterations of adding an enzyme substrate can be used to verify the initial response or calculate the projected recovery.

Experiments have shown that by adding a second aliquot of enzyme substrate to a unit of analysis, the reproducibility of the results can be maintained. In some modalities, a control method provides replication analysis using a unit of analysis that gives a response significantly lower than that expected.

With any of the control methods described in this, there are numerous possible errors that can be taken into account or postulates of excluding a control method. Exemplary analysis errors include, but are not limited to, improper manufacture of a unit of analysis or device, improper aspiration of a sample and / or one or more reagents, a unit of analysis is not properly positioned in relation to the photomultiplier during the detection, and a missing unit of analysis in the device or system.

In some modalities, a method to automatically monitor compliance with the. Individual with a medical treatment using the devices or systems present is provided using the FS devices. The method comprises the steps of allowing a body fluid sample to react with assay reagents in a device to produce a detectable signal indicating the presence of an analyte in the sample; detect the signal with the device; compare the signal with a known profile associated with medical treatment to determine whether the individual is complying or not complying with said medical treatment; and notify the individual or associated individuals, for example, local health care agents of said compliance or non-compliance. This can be: important for the HS systems of the invention, because the mitigation policies will not be as effective if the recommended treatments are not followed. In some modalities, non-compliance events are reported to OS systems. The model can be updated to take into account non-compliance. Officials who monitor OS model results can also contact local officials to take action.

In another embodiment, the system and methods of the invention can identify trends in biomarker levels and daily information in a patient over time that can be used to adjust the dose of the drug to an optimal level for particular patients (e.g. adaptable to the dose variation).

In some embodiments non-compliance may include taking an inappropriate dose of a pharmaceutical agent including without limitation multiple doses or no doses, and may include inappropriately mixing pharmaceutical agents. In preferred embodiments a patient is notified substantially immediately after the signal is compared to a known profile.

An individual monitored by the Health Shield may forget to take a sample of body fluid for analysis as described herein. In some embodiments, a method for alerting an individual to prpbar a body fluid sample using a device as described herein comprises providing a protocol to be executed on the device, the communicated protocol of the OS component, associated with said individual. and comprising the time and date to test the body fluid sample; and notify the individual to test said body fluid at said date and time if said sample has not been tested. In some embodiments, an individual may be notified as described herein, for example in a wireless connection. Compliance with therapeutic regimens can be. improved by using indications on a screen and obtaining patient responses (for example, by means of a contact screen).

In one embodiment, the system includes a convenient way to package the FS elements required for multiple complex analyzes in a secure manner for packaging. For example, the analysis elements snap to a housing. (c) Field System Analysis A variety of analyzes can be performed on a fluid device described herein to detect an analyte of interest in a sample. A wide variety of markers are available in the art that can be used to carry out the present analyzes. In some embodiments, markers are detectable by spectroscopic, photocchemical, biochemical, electrochemical, immunochemical or other chemical means. For example, useful nucleic acid markers include 32P, 35S, C14, H3, 1125 and 1131 radioisotopes, fluorescent dyes, electron-dense reagents and enzymes. A wide variety of appropriate markers for the labeling of biological components are known and are widely reported in both. scientific literature as patent literature and are generally applicable to the present. invention for the marking of biological components. Appropriate markers include radionucleotides, enzymes, substrates, co-factors, inhibitors, fluorescent portions, chemiluminescent portions, bioluminescent markers, colorimetric markers. or redox markers. Reagents that define specificity of analysis optionally include, for example, monoclonal antibodies, polyclonal antibodies, proteins, nucleic acid probes or other polymers such as affinity matrices, carbohydrates or lipids. The detection can proceed by any of a variety of known methods, including spectrophotometric markers or optical screening of radioactive, fluorescent or luminescent labels or other methods that track a molecule based on size, charge or affinity. A detectable portion can be of any material having a detectable physical or chemical property. Such detectable labels have been well developed in the field of gel electrophoresis, column chromatography, solid substrates, spectroscopic techniques and the like, and in general, useful labels in such methods can be applied to the present invention. Thus, a marker includes without limitation any composition detectable by means of spectroscopy, photochemistry, biochemistry, immunochemistry, based on nucleic acid probe, electrical, optical thermal or other chemical means.

In some embodiments, the label is directly or indirectly coupled to a molecule to be detected such as a product, substrate or enzyme, according to methods well known in the art. As indicated above, a wide variety of markers are used, the choice of marker depends on the required sensitivity, ease of conjugation of the compound, stability requirements, available instrumentation and disposal stipulations. Non-radioactive markers are frequently annexed by indirect means. In general, a receptor specific for the analyte is linked to a portion that generates a signal. Sometimes the analyte receptor is linked to an adapter molecule (such as biotin or avidin) and the set of assay reagents includes a binding portion (such as a biotinylated reagent or avidin) that binds to the adapter and analyte. The analyte binds to a specific receptor at the reaction site. A labeled reagent can form a sandwich complex in which the analyte is in the center. The reagent may also compete with the analyte for receptors at the reaction site or bind to vacant receptors at the reaction site not occupied by the analyte. The label is either inherently detectable or linked to a signal system, such as a detectable enzyme, fun fluorescent compound, a chemiluminescent compound or a chemiluminogenic entity such as an enzyme with a luminogenic substrate. A number of ligands and anti-ligands can be used. Where the ligand has a natural anti-ligand, it can be used in conjunction with labeled anti-ligands. Exemplary ligand-anti-ligand pairs include without limitation biotin-avidin, thyroxine-anti-t4, digoxigenin-anti-digoxin and cortisol-anti-cortisol, Alternatively, any haptenic or antigenic compound may be used in combination with an antibody.

In some embodiments, the label can also be directly conjugated to compounds that signal general, for example, by conjugation with an enzyme or fluorophore. Enzymes of interest as markers will be mainly hydrolases, particularly phosphatases, esterases and glycosidases or oxidoreductases, particularly peroxidases. Fluorescent compounds that include fluorescein and its derivatives, rhodamine and its derivatives, dansyl and umbelliferone groups. Chemiluminescent compounds include dioxetanes, acridinium esters, luciferin and 2,3-dihydroftalazindiones, such as luminol.

Methods for detecting markers are well known to those of skill in the art. Thus, for example, where the marker is radioactive, means for detection include scintillation counts or photographic films such as in autoradiography. Where the marker is fluorescent, it can be detected by exciting the fluorochrome with light of an appropriate wavelength and detecting the resulting fluorescence by, for example, microscopy, visual inspection, via photographic film, by the use of electronic detectors such as digital cameras, charge-coupled devices (CCD) or photomultipliers and phototubes or other detection devices. Similarly, enzymatic labels are detected by providing suitable substrates for the enzyme and detecting the resulting reaction product. Finally, simple colorimetric markers are often detected simply by observing the color, that is, the absorbance, associated with the marker. For example, conjugated gold often appears rpsa, while other conjugated pearls resemble the color of the pearl.

In some embodiments, the detectable signal may be provided by luminescence sources. Luminescence is the term commonly used to refer to the emission of light from a substance for any reason other than an elevation in its temperature. In general, atoms or molecules emit photons of electromagnetic energy (for example, light) when moving from an excited state to a lower energy state (usually the basal state). If the cause of excitation is a photon, the luminescence process is called photoluminescence. If the cause of excitation is a photon, the luminescence process can be referred to as electroluminescence. More specifically, electroluminescence results from the direct injection and removal of electrons to form an electron-hole pair and subsequent recombination of the electron-hole pair to emit a photon. The luminescence that results from a chemical reaction is usually referred to as chemiluminescence. The luminescence produced by a living organism is usually referred to as bioluminescence. If the photoluminescence is the result of a spin-allowed transition (that is, a singlet-singlet transition, triplet-triplet transition), the photoluminescence process is usually referred to as fluorescence. Commonly, fluorescence emissions do not persist after the cause of excitation is removed as a result of short-lived excited states that can be rapidly relaxed by such spin-allowed transitions. If photoluminescence is the result of a spin-forbid transition (for example, a triplet-singlet transition), the photoluminescence process is usually referred to as phosphorescence. Commonly, phosphorescence emissions persist long after the cause of arousal is removed as a result of excited, long-lived states that can be relaxed only by means of such spin-forbid transitions. A luminescent label can have any of the properties described above.

Appropriate chemiluminescent sources include a compound that becomes electronically excited by a chemical reaction and can then emit light that serves as the detectable signal or donates energy to a fluorescent acceptor. A diverse number of families of compounds have been found that provide chemiluminescence under a variety of conditions. A family of compounds is 2,3-dihydro-l, 4-phthalazinedione. A frequently used compound is luminol, which is a 5-amino compound. Other members of the family i 'include 5-amino-6,7,8-trimethoxy- and the dimethylamino [ca] benz angle. · These compounds can be made luminescent with alkaline hydrogen peroxide or calcium hypochlorite and base. Another family of compounds are the 2,4,5-triphenylimidazoles, with loofin as the common name for the parent product. Chemiluminescent analogs include para-dimethylamino and -methoxy substituents. The chemiluminescence can also be obtained with oxalates, usually active oxalyl esters, for example, p-nitrophenyl and a peroxide such as hydrogen peroxide, under basic conditions. Other useful chemiluminescent compounds that are also known include -N-alkyl acridinium esters and dioxetanes. Alternatively, luciferins can be used in conjunction with luciferase or lucigenins to provide bioluminescence.

The term "analytes" as used herein includes without limitation drugs, prodrugs, pharmaceutical agents, drug metabolites, biomarkers such as expressed proteins and cell markers, antibodies, serum proteins, cholesterol and other metabolites,. polysaccharides, nucleic acids, biological analytes, biomarkers, genes, proteins or hormones or any combination thereof. The analytes can be combinations of polypeptides, glycoproteiries, polysaccharides, lipids and nucleic acids.

Of particular interest are biomarkers associated with a particular disease or with a specific disease stage. Such analytes include but are not limited to those associated with infectious diseases, autoimmune diseases, obesity, hypertension, diabetes, neuronal and / or muscular degenerative diseases, cardiac diseases, endocrine disorders, metabolic disorders, inflammation, cardiovascular diseases, sepsis, angiogenesis, cancers , Alzheimer's disease, athletic complications and any combination thereof.

Also of interest are biomarkers that are present in variable abundance in one or more of the body tissues including heart, liver, prostate, lung, kidney, bone marrow, blood, skin, bladder, brain, muscles, nerves, and selected tissues that are affected by several. diseases, such as different types of cancer (malignant or non-metastatic), autoimmune diseases, inflammatory or degenerative diseases.

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Timpka, T., M. Morin, J. Jenvald, H. Eriksson and E.A. Gursky. 2005. Towards a Simulation Environment for Modeling Local Influenza Outbreaks. AMIA 2005 Symposium Proc. 729-733 EXAMPLES Example 1. National Influenza Health Monitoring System In this example, the Health Shield system is tailored for the national disease control agency and deployed as a national health shield. The objective of the program is to create a system for the containment and pro-active management of diseases such as influenza that can cause epidemics. The system is designed to identify, track and contain the spread of the outbreak of influenza and significant "mutant" strains (such as those with resistance to antiviral drugs or those with more virulence) in: the earliest stages of infection, improving by this the prevention and response of disease. The inputs to the modeling efforts of the operating system (OS) are used to determine an optimal sampling and containment strategy for influenza.

A second objective of the present system is to improve results and reduce the costs of health care by better managing and preventing the advancement of chronic diseases, starting with diabetes. The ability to improve outcomes and dramatically reduce health care costs by preventing and investing diabetes alone can reduce annual health expenses by trillions of dollars. HS systems deployed for influenza and diabetes can also be tailored to prevent and better manage other chronic diseases such as congestive heart failure (CHF).

The components of the Field System are deployed nationally, with initial deployment focused on geographical locations and / or populations considered to be at risk. The FS systems are deployed in part as automated analysis robotically executed in central laboratories. The systems have automated on-board controls to improve the reliability of the results. Mobile Field Systems are also deployed in multiple care points, including hospitals, clinics, doctors' offices and public locations such as schools, pharmacies, airports, etc. The FS components are also deployed for family home use in rural areas where there is limited health care infrastructure, allowing individuals in those areas to be tested remotely and as necessary to communicate with health experts wirelessly without having to travel to a clinic or hospital.

For the monitoring of H1N1 influenza ("swine influenza"), FS measures antigens and antibodies to H1N1 in blood and saliva samples. The blood and saliva samples are tested in two separate cartridges. Blood tests are multiplexed with tests for a combination of cytokines that measure the body's response to infection.

For HlNl, FS cartridges are tailored to perform six analyzes and two controls, including analysis for antibody and HlNl antigen and four cytokines that measure the body's response to infection. i The multiplex analyzes are executed in less than 90 minutes or less than 30 minutes depending on the specific configuration of FS. The cartridges for blood and saliva are processed separately or jointly depending on the specific FS configuration. As new virus strains emerge, additional analyzes are added to existing panels. For example, the H1N1 analyzes are further multiplexed with analyzes for H5N1 antibodies (avian or avian influenza). High volume reader systems are provided in addition to the individual sample readers. The high volume readers are configurable to run dozens of samples simultaneously.

The test results are transferred to the centralized government operating system in secure high-speed networks in real time along with other clinically relevant patient data collected through the instrument's contact screens or through the portal's programming elements. OS web that extracts information from patient records. The integrated data sets are passed through pattern recognition algorithms to determine the status < of individual illness and to verify other abnormalities. The integrated analytical system has controls integrated in it to verify and identify sources of variability in the data. The actions taken when variability or noise in the data are identified are integrated in the alert capacity of the system based on ready-made rules established for the government organization before deployment. The rules specify when and how to notify a physician, patient and / or patient contacts automatically by telephone, email or similar electronic communications when an actionable event is detected.

In the implementation of a containment strategy for influenza, the parameters of the system are adjusted to control against false negatives. The deployment strategy is weighted against that uncertainty. Monte Carlo modeling is used to estimate the robustness of the strategy by quantifying uncertainty.

Table 7 below details the configuration and pilot plan to implement the development of the influenza monitoring phase. Tasks in the table can be accomplished in parallel to accommodate a faster timeline.

Table 7: Development of the influenza monitoring phase Two deployment scenarios for this program are as follows: Scenario A: Pegueño pilot program to deploy the Health Shield with many measurements in several locations (100,000 measurements of analysis in people and / or animals monitored through 5-7 centers / high risk locations in a confined area). The program lasts six months. Stages: to. Preparation of the Health Shield according to government requirements b. Pilot program executed with 100,000 measurements and 100 readers c. Training of 5-7 centers / high risk locations d. Modeling and simulation to identify the most effective containment and prevention strategy in terms of health outcomes and costs and. Modeling and simulation to identify the most effective alerts and recommended actions to be taken based on the various test results.

Scenario B: Equip a contained region and high risk locations of the surroundings for containment and prevention of the spread of influenza while improving the treatment of those infected. Show that the Shield of. Health effectively contains the outbreak of influenza and prevents the spreading of a virus by means of an extensive program in and around the local area using a larger number of measurements and locations than those required by scenario A (500,000 measurements in people and / or animals through 25-30 centers / high-risk locations). The program lasts six months. Stages: to. Preparation of the Health Shield according to government requirements b. Pilot program with 500,000 measurements and 500 readers c. Training of 25-30 centers in and around the contained region d. Modeling and simulation to identify the most effective containment and prevention strategy in terms of health outcomes and costs and. Modeling and simulation to identify,. the most effective alerts and recommended actions to be taken based on the various test results F. Activate readers to function to contain disease due to any outbreak of influenza and the management of other chronic diseases.

A component of integrated programming elements is developed for FS systems and OS systems, the user inferred from which is shown in Figures 16 and 17. The integrated programming element component consists of two applications. An application shown in Figure 16 is used primarily in regional and local triage centers to collect individual patient data and make specific recommendations for treatment based on information collected from the patient and analysis data collected by the FS. There is a central office component where data is loaded to provide the OS model with national and regional data describing the current status of 'the epidemic. These periodically updated data are used to refine the model to improve prediction accuracy. Reports of the collected data are generated and actions are taken in local centers.

The application illustrated in Figure 17 is used in the central or national office. This application is the user interface to execute the model and produce reports generated as outputs of the model. It is here that the user can be coupled with "what if" scenarios to determine actions and mitigations appropriate to the epidemic.

The ability to proactively detect and contain the spread of mutant influenza strains provides a life-saving and economic protection capacity that has not been met using existing methodology. These benefits are especially important in decentralized and remote locations where the care of optimal health is not readily available. The proactive health management strategy for chronic diseases is estimated to reduce current health care costs by one-third to one-half of today's expenditures and ensure that all individuals obtain a consistent and uniform high level of care Of the health.

Example 2. Simulation of the La Gloria outbreak with and without Mitigation Policies Figure 18 illustrates the real world vs simulated results of an influenza outbreak in La Gloria, Mexico that occurred between February and May of 2009. La Gloria is a town of approximately 3,000 in the Mexican state of Veracruz. Hundreds of people from the town were diagnosed with respiratory problems, including positive tests for swine influenza (H1N1) and the most common influenza variant H2N3. Figure 18 shows a comparison of the outbreak-real data (circles) in comparison, with a model without HS mitigation (solid line). The model without mitigation is. in accordance closely with the actual data. A model with HS surveillance and mitigation policies is shown with dashed lines. The model is determined by iterative adjustment of the current outbreak to the model of Figure 2 until an optimal fit is obtained. With the HS in place, both the severity and rapidity of the outbreak are projected to be dramatically reduced. The projected improvement is based on the parameters of the model as determined for the un mitigated outbreak and using the model to predict the outcome assuming surveillance using the HS system and isolation at home of those who are infected.

Critical model parameters: basic reproduction number R0 = 2.2 average generation time in days Tg = 2.0 fraction of the generation time that is latent (non-infectious) fL = 1/3; For the unmitigated outbreak no surveillance was carried out I no action was taken on the infected population.

For illustrated mitigation 60% of symptomatic (infected suspects) reported for voluntary testing Subjects with positive results - (based on analysis sensitivity of 0.8 (80%) were quarantined at home.

Example 3. Prevention and Investment of Diabetes For diabetes and its complications (for example, renal and cardiovascular disease), the cost-benefit ratio of the Health Shield is quantified both through government programs and private programs. The programs are designed to dramatically reduce the cost of Type 2 Diabetes Mellitus (T2DM) by preventing, slowing and reversing the progression of the disease through individualized lifestyle modification therapy and remotely administered using the HS system.

T2DM and the frequently associated obesity (coined the "diobesity epidemic") lead to cardiovascular, metabolic, ocular, neurological and renal complications also frequent as increased cardiovascular morbidity and mortality. T2DM results in a heavy economic burden on the health care system. In the United States of America, thirteen percent of adults have diabetes and 1.6 million new cases are diagnosed each year. The estimated total cost of diabetes in 2007 in the. The United States of America was $ 174 billion and 284,000 deaths in 2007 were attributed to diabetes. See American Diabetes Association, Diabetes Care 31, 596 (March 1, 2008).

The Services of the Armed Forces of the United States of America are not immune from the epidemic of diobesity. For example, there are 140,000 diabetic patients cared for by the USAF. On average, diabetes is responsible for $ 6,649 in excess expenses per year per person with diabetes. Thus, if only 20% of those with diabetes have their illness delayed or reversed, the savings reach $ 186,172,000 dollars annually. In just five years it is anticipated that the savings will reach $ 1 trillion dollars. The costs of delaying the onset of costly micro- and macrovascular complications are expected to produce even greater benefit. Id.

There is evidence that lifestyle interventions reduce the risk of developing diabetes by up to 58%. J. Tuomilehto et al., N Engl J Med 344, 1343 (May 3, 2001); W. C. Knowler et al., N Engl J Med 346, 393 (February 7, 2002). Large epidemiological population studies have shown that insulin resistance and the presence of metabolic syndrome parameters identify subjects at higher risk of developing T2DM and cardiovascular and cerebral events. P. Wilson W., R. B. D'Agostino, H. Parise, L. Sullivan, J. B. Meigs, Circulation 112, 3066 (Nov. 15, 2005); C. Lorenzo, M. Okoloise, K. Williams, M. P. Stern, S.M. Haffner, Diabetes Care 26, 3153 (Nov, 2003). The cardiovascular health study showed that 9 out of 10 new cases of diabetes in subjects 65 years and older are attributable to 5 lifestyle factors whose improvement can dramatically reduce the risk of diabetes by up to 89%. D. Mozaffarian et al., Arch Intern Med 169, 798 (April 27, 2009). These factors include physical activity, diet, smoking, alcohol use and adiposity. In the Diabetes Prevention Program (DPP), it is estimated that lifestyle intervention delays the development of T2DM by 11 years and that it reduces the absolute incidence of diabetes by 20%. P. Lindgren et al., Int J Technol Assess Health Care 23, 177 (Spring, 2007). - Thus, an 'immediate promising strategy to improve national health includes premature intervention with individuals at some risk of developing T2DM. The pre-diabetic population, as defined by fasting glucose levels without impairment (IFG) and / or impaired glucose tolerance (IGT), is still at higher risk of developing T2DM than its normoglycemic counterparts. Nevertheless,; the proportion and time of conversion are difficult to predict at the level of individual subjects. To integrate in these significant epidemiological findings, the Shield; of Health provides a new paradigm of diagnosis and treatment that can be focused on the individual subject using dynamic collection and analysis of physiological measures. This procedure detects and predicts earlier the subject's risk and trajectory towards the development of T2DM and subsequent cardiovascular, metabolic, ocular, neurological and renal events. At the same time, the Health Shield gives each patient individualized tools and strategies to make the necessary lifestyle changes. The HHS reinforces the relevant health messages sent to users by providing physiologically relevant information about the effect of these changes. Lifestyle in each individual / family base.

The management of subjects with T2D is carried out by an extensive health care team (HCT) including physicians, nurse practitioners, physician assistants, nurses, dieticians, pharmacists and mental health professionals. Additionally, individuals with diabetes take an active role in their care and receive an extensive diabetes self-management education to act on it. The Health Shield helps in that education and management through the flexible care testing point (POCT) and feedback technology.

For diabetes and its complications, 6 tests 1 are executed for each time point with an operation time of less than 30 minutes. Additional cartridges are provided for kidney and cardiovascular disease, each with 6 additional tests, which are processed in 15 minutes or less to detect the risk of a cardiovascular event or renal failure and determine the need for a hospital visit. This allows patients to be treated before their disease progresses to the point that they need to visit expensive emergency salts.

POCT is defined as a testing system near the patient and has been available for many years, depending on bank devices and portable devices. POCT as diagnostic tools and clinical decision aids are now an integral part of the administration of health care in outpatient care, primary care, emergency care and operating rooms. A competent example is the monitoring of blood glucose during gestational diabetes mellitus that reduces the proportion of complications to the mother and baby.

The Health Shield extends POCT resources to the pre-diabetic population when administered, for example: 1. A Point of Care system that serially and conveniently determines, in real time, a variety of circulating blood markers that quantify better, dynamically, insulin resistance, metabolic syndrome, inflammation and cardiovascular risk. The device is also used as an interface to the Mobile Health Care system (item 3 below). 2. A mathematical / statistical learning engine that prematurely characterizes and quantifies the risk of a given subject by developing T2DM and associated complications. The working product of the learning engine will be the set of biological markers that better predict the onset of diabetes and the model that incorporates that predictive power. This type of analysis is commonly developed during a statistical model construction exercise around competent survival curves as defined by a statistical Kaplan-Meier and in the context of a Cox proportional hazards analysis. The learning engine described here takes advantage of this probability landscape by taking samples at sufficiently high frequencies to establish the most informative marker patterns in most of the subset of parsimonious markers and hence derives a danger / dynamic risk space for each individual subject in a cohort. The complementary co-variants that are taken into account in the model include age, smoking status, alcohol use, body mass index (BMI), dietary habits, exercise levels, glucose levels, blood pressure and lipid levels. As additional data becomes available to models, the system improves probability patterns to learn more fully about each cohort of subjects and adjust itself appropriately. 3. A Mobile Health Care System that uses the integrated data, algorithms and models described above in concert with interactions with the subject to help with behavior modification and increase adherence to diet, exercise and therapy. When interconnecting with a path either a device contact screen or a network-integrated mobile device such as a cell phone or PDA, the system performs the following: • Determine the situation and state of mind behind the question of the subject • Obtain key indicators when asking questions • Transmit truly individualized and context-specific content to the device's contact screen or mobile device / phones to help users modify behavior.

The individualized content is determined by applying artificial intelligence techniques such as rule-based inference to the measured data of the subject of the device, as well as other data provided, "the answers to the questions posed to the subject and if available, the location geographical location of the originating call as provided by the GPS on board.

By integrating and analyzing response data, the learning engine will provide subject-specific feedback when selecting a particular item from a library that is relevant to the subject's mood, circumstance, and location. The items presented include nutritional advice, exercise advice, general lifestyle advice, psychological counseling, selection of restaurants in the subject's neighborhood, as well as menu items recommended in that restaurant, electronic food stamps and lifestyle products , collection of nutritional or exercise data and reinforcement / encouragement in advance towards obtaining health objectives.

The use of these tools and the data sent back to the doctors help the HCT to offer each individual subject therapeutic changes made prematurely that prevent the development of T2DM and its deadly complications.

Example 4. Visualization and Prediction Model of Diabetes Risk In a study of 187 people not known to be diabetic, the subjects underwent a Oral Glucose Tolerance Test (OGTT). When an OGTT is performed, the individual fasts for up to fourteen hours in advance and only ingests water. At the beginning of the test, the individual is given a blood sugar test to determine a reference number. Then, a sugar solution is given orally. The blood is then returned to test in a time course. For diabetes, important numbers will come two hours into the test. For a hypoglycemic individual, blood sugar may not fall for up to six hours.

More information is available in diabetes-diagnosis. suitelOl. com / article. cfm / the_glucose_tolerance_test #ixzzOSWaqWbQr A series of measurements of glucose and the GLP-1 hormone were made starting with a fasting glucose level then at several points in time following glucose ingestion. Measured variables included: • Active GLP and total LPG at 5 minutes before and 10, 20, 30, 60, 90 and 120 minutes after consumption of glucose solution.

• Basic profile data: age, height, weight, gender,% body fat.

• Creatinine concentration.

Genetic markers: identification of single nucleotide polymorphism (SNP) variations for 12 different SNP locations.

· Diagnosis of fasting and post-test glucotolerance (normal or impaired fasting glucose, normal or impaired glucotolerance or diabetes mellitus) The glucose tolerance test shows that many subjects have either diabetes or impaired glucose tolerance (IGT). The rest have normal glucose tolerance (NGT). The results of GLP-1 along with demographic information (age, sex, height) and determinations of the 12 SNPs are evaluated by recursive distribution using Classification and Regression Trees (CART) and generated the recursive division tree shown in Figure 19. The tree is designed to correlate with and / or predict glucose tolerance. CART is described by Breiman, Friedman, Olshen and Stone in Classification and Regression Trees, Chapman & Hall / CRC; The edition (January 1, 1984). This technique and similar techniques develop a model by recursively dividing the data according to indicators that will more accurately separate the data. For exampleIn this example, the problem is to classify the patient's glucotolerance state. Among the many predictors, the variable "age" with the test criterion of 66.5 years (that is, is a person 67 years of age or older?) Gives the division with the least classification errors in the model described in the study. . For each resulting sub-population in each division, the next most effective division is identified. By using only part of the data to adjust the model and the rest for testing, the algorithm avoids the overfitting of data from "training" .

The analysis revealed that in the studied population, five factors produced an optimal categorization of the subjects: (1) age; (2) levels of GLP-1 (active) determined at 120 minutes following the administration of glucose; (3) height; (4) body fat (calculated from height and weight); and (5), an SNP: rsl0305420.

Visualization has multiple purposes. For example, the doctor can use the tree to explain to a patient their risk factors for diabetes. For example, count the leaf nodes (terminal) from left to right, the doctor can explain to the patient that he is currently in leaf node # 4 ("IGT (11/2/1)"), and that as Your age will end either at node # 1 or # 2, depending on your height. For a shorter patient, this may indicate a very severe risk of developing diabetes and they may be recommended to take a therapeutic intervention, such as lifestyle changes and / or therapeutic treatment.

The tree can also be used to investigate different populations at risk for diabetes. Each of the divided criteria indicates a different type of risk and a different mechanism to separate the larger population into sub-populations. As a result, the effect of each division criterion could be examined in terms of a causal relationship. In addition, patients who are misclassified as diabetic are classified as such due to significant risk factors that could contribute to their disease. As a result, it would be valuable to study this group to determine what other factors can mitigate your risk. For the development of long-term longitudinal study, the tree can be used to investigate the progress of the disease. When selecting patients whose condition is still NGT or IGT, but who are at high risk (for example, poorly classified as IGT or DM, respectively), the researcher can follow them in time to see which members of the sub-population get worse and which no, in order to understand the effects and causes of risk factors for impaired glucotolerance. Similarly, the tree can be used for comparative analyzes for sub-populations of patients.

Weights (or population counts) can be assigned to a larger sample of a population in order to determine the risk that may vary due to different sampling strategies. For such recursive division models, the risk can be determined in different geographical regions and parameters of SIR can be calculated with such trees or with assemblies of CART (classification and regression trees) and other methods, such as center methods and other methods which involve measures of similarity, generalized linear models, non-parametric and parametric Bayesian methods and more.

Example 5. Adjusted cost-matrix confusion matrices The model of the invention can be adjusted for the cost associated with different errors, based on economic cost, temporary costs or other factors, in order to minimize the cost of errors made by a model. This example presents a cost analysis using the data presented in the example above. The results are shown in Table 8.

Table 8 In the table, the category of patient predicted is compared with the diagnosis based on OGTT. The table was built without regard to the costs of errors.

A similar matrix of predictions is presented below when the model is developed incorporating a weighting based on the misclassification costs recommended by an expert in the field. Here, the rule states that it is more expensive to predict NGT when DM is the correct state for the patient. The reasoning is that certain types of errors are far worse than others, such as the eventual cost of sending a diabetic patient home with a clean health account versus the cost of follow-up testing by a patient classified as diabetic.

Table 9 Examples of such weights are given below in Table 10 using the costs imposed to generate Table 9. If a diabetic patient is predicted to be NGT, a penalty of 100 is determined, while a prediction that an IGT patient is Diabetic is determined at a much lower penalty of 10: the cost of secondary testing and lifestyle changes would not be as significant as the cost of medical care for the diabetic. These costs can be changed with the optimization of the prediction model for other contexts.

Table 10 Example 6. Prediction of the Start of Infection and Sepsis and Enabling of Premature Treatment For infection, an approach of the Health Shield programs in civilian and military populations has been aimed at improving outcomes in injured / burned / seriously ill populations and quantifying the impact of premature intervention / treatment (~ 36-24 hours) on the survival of those people.

By means of more frequent sampling made possible by the requirement of small volume) and a wirelessly integrated analytical modeling engine, Health Shielding Systems can be used to anticipate the onset of sepsis up to 36 hours before clinical diagnosis .

In this example, hospitalized patients undergoing chemotherapy for acute myeloid leukemia 1 are monitored for the inflammatory markers IL-6, IL-? ß, and protein-C, a protein involved in coagulation control. In patients who become septic (N = 4), a combination of events occurred that do not occur in patients who do not progress to sepsis (N = ll). Events include: 1) temperature projection to > = 38 ° C; 2) IL-6 raised to > 5 ng / ml during a rapid projection (occurring in an interval of <12 hours); 3) decline of C-protein α < 1 ug / ml; and 4) IL-? ß raised to > 100 pg / ml. Individual events are indicators of the presence of sepsis. 11-6 is projected to more than about 10,000 pg / ml in all subjects who became septic (Figure 36A). The C-protein declines to a minimum of approximately 1.3 pg / ml in all subjects that become septic (Figure 36B).

However, the projection of fever is not predictive of sepsis. The combined information (temperature, IL-6, protein-C and IL-? ß) is effective in the prediction of sepsis.

The combination of events was: IF the temperature > 38 OR decline in protein-C > 30%, and subsequently IL-6 was > 5 ng / ml OR IL-? ß was > 100 pg / ml, the patient advanced to sepsis. '| Table 11 shows the time that elapses from an indication, advance to sepsis as defined earlier to diagnose those patients 1 who progressed to sepsis. The combination of events provides a significant window before the diagnosis in which therapy can be initiated.

Table 11 Sepsis is an inflammatory state of the entire body that includes a blood infection. Sepsis can lead to septic shock, which is fatal in approximately 50% of cases. Sepsis and septic shock represent a challenging problem in critical care medicine and are a leading cause of mortality in the intensive care unit. In the United States of America, sepsis develops in 750,000 subjects and septic shock results in approximately 215,000 deaths per year. The increased cost of bloodstream infections (BSI) has been estimated to close at $ 20,000. . Kilgore, 'S. Brossette, Am J Infect Control 36, S172 on (December 2008). Patients with BSI acquired in the intensive care unit (ICU) have a significantly increased average length of ICU stay (15.5 vs. 12 days) and median costs of hospital care ($ 85, 137 vs. $ 67, 879) compared to patients without ICU-acquired BSI. Id.

The initiation of therapy prematurely reduces mortality related to septic shock. The flexible toolkit, convenient and intelligent provided by the HS allows for better and earlier care at a lower cost. An outstanding element of the system is the ease of use and the direct and active participation of individual patients and the HCT. A 25% improvement in the number of lives saved correlates with a 25% decrease in the cost of caring for those patients who would otherwise have died. In addition to those savings in cost there is a decrease in the cost of care for those who survive but require expensive treatment with which the HS system can be treated more quickly and thus bring less cost in the health center. The total cost reduction associated with HS in the management of infection is estimated to be greater than 50% or more than $ 7.5 billion per year in the United States of America.

HS can identify a predictive signature of the onset of infection and sepsis in patients. A similar signature can be used to detect the presence of infection and the body's response to infection in people infected with various strains of influenza in such a way that treatments can also be made and done earlier.

Example 7. Influenza Surveillance: Infection Detection Analysis Viral particle detection. Figure 20A shows the detection of a Hl antigen in response to H1: N1 particles. The analyzes for the Hl antigen are carried out as described in PCT patent publication WO / 2009/046227, filed on October 2, 2008 entitled "MODULAR POINT-OF-CARE DEVICES AND USES THEREOF". Samples that contain known antigen concentrations, ???? they are mixed with the detector antibody and the mixture is incubated for 30 minutes. In cavities of 384 cavities microtitre plates coated with capture antibody. The cavities are washed by repeated aspiration of the buffer solution and then the enzyme substrate is added. After 10 minutes, the microtiter plate is read on an M5 luminometer. The capture antibody is a monoclonal anti-Hl antibody attached to a substrate. The detector antibody is a polyclonal anti-Hl antibody with APase. The analyte is a particle preparation that shows both Hl and NI antigens. Variable quantities of analyte projected to the pH buffer are shown in Figure 20 on the X axis.

Analysis for H1N1 in nasal sample. A nasal sample obtained using a swab is extracted using • the reagents and protocol of a commercially available kit kit (Quickvue). A buffer solution for the pH and the nasal extract with and without added H1N1 antigen are analyzed (four replicate / sample measurements) according to the protocol described above with the following results: Table 12 Analyte Counts average aggregate CV of Signal analyte ng / ml signal% PH buffer solution of 0 analysis 61 1 14 Extract of nasal cotonete 0 324 72 PH buffer of 500 analysis 29602 5 Extract of nasal cotonete 500 18595 7 The response of the analysis to samples without added antigen is essentially negative and a clear distinction is observed between samples with added antigen and no added antigen.

In a similar example using clinical samples, two analyzes are performed on each multiplexed cartridge with "tips" in duplicate for analysis for Hl. The results are shown in Figure 20B. In the figure, "tips 1, 2" gives an average signal (counts) for a pair of antibodies and "tips 3, 4" gives a count for a different analysis pair. Nasal swab samples from eight A-negative influenza samples and 11 positive samples from 2009 influenza (H1N1) are analyzed using the PCR method. There is good discrimination between positive and negative samples for the samples presented using the data of both analyzes using the dotted line as a discriminator (cut). Using this threshold, there are eight true negatives, two false negatives, nine true positives and no false positives. The sensitivity (TP / TP + FN) is 81% and the specificity (TN / TN + FP) is 100%. Discrimination using either the analysis is only less effective than combining the results of both analyzes.

Host Antibodies. Host antibodies against influenza particles can be detected according to the invention. The presence of such antibodies may indicate that an individual has a decreased likelihood of active infection leading to the disease. Figure 21 shows an assay designed to detect host antibodies in an FS cartridge. In this example, the capture reagent is a subrogated antigen comprising an anti-idiotype "of the antibody to be measured bound to the solid phase.The detection reagent is an anti-human IgG antibody labeled with alkaline phosphatase.The humanized monoclonal antibody. purified (analyte) is added in known concentrations to human serum as shown on the X axis. Cavities of microtiter plates coated with antibody to the viral antigen Hl are incubated with diluted sample (human blood, plasma or serum) mixed with alkaline phosphatase labeled antibody to Hl for 30 minutes at room temperature. The cavities are washed with pH buffer and exposed to the alkaline phosphatase substrate chemoluminog, only for 10 minutes before reading the photon production rate with a luminometer 5 (Molecular Devices). Influenza antibodies can be measured by the same method using the influenza antigen bound to the solid phase.

In another set of experiments, antiserum host to H1N1 are detected directly. The capture surfaces are coated with viral antigen. A sample of positive antibody serum is diluted 10 times and incubated with the capture surface for 10 minutes, followed- by incubation with anti-human IgG APase-labeled for 10 minutes.

After washing the capture surface, an enzyme substrate is added and the analysis signal (photon production) is measured after 10 minutes. The results are shown in Figure 22A. As seen in the figure, the signal increases with the load of antigen on the surface and reaches a plateau level at approximately 1000 ng / ml of antigen.

Figure 22B shows the results of an analysis carried out as before using an antibody-positive sample diluted to different extensions. As seen in the figure, the analysis response is titrated at a maximum level at approximately a 10-fold dilution. As a specific control, measurements are "made in parallel to 0 and 500 ng / ml coating concentration of viral coating antigen." Essentially there is no response to any sample dilution without antigen present.

Inflammatory Markers Projections in inflammatory markers, for example, immune markers such as cytokines, may indicate that an individual is infected with a strain of influenza that is not identified by current antigen assays or is undergoing another acute process that requires medical support. Figure 23 shows the results of an analysis for the human cytokine IL-6 using an FS cartridge device according to the invention. In this example, the capture reagent is a monoclonal antibody to human IL-6 and the detection reagent is a polyclonal anti-human IL-6 antibody labeled with alkaline phosphatase. Purified IL-6 is added to human plasma which initially contains essentially no IL-6 in variable amounts as shown in the X axis of Figure 23. The plasma samples are analyzed in the FS system with the results shown.

In another example, a hospitalized human subject suspected of having swine influenza is monitored with the HS system. Two different types of cartridge are used in serial nasal samples collected from the subject. One type of cartridge has three different multiplexed assays for the H1N1 antigen (using different pairs of antibodies), the other type has analysis for the inflammatory markers 11-6 and TNF-OI. As seen in Figure 37, the level of antigen (as measured by the counting rate of the analyzes) is increased several times during days 6-10 of the monitoring period. In the same time interval, both levels of cytokine are projected, indicating by this an acute inflammatory process.

Example 8. Analysis of Sepsis Marker Sepsis is a serious medical condition characterized by an inflammatory state of the entire body and in the presence of a known or suspected infection. Sepsis can lead to septic shock, multiple organ dysfunction syndrome and death. Protein C is a major physiological anticoagulant. The key enzyme of the protein C pathway, activated protein C, provides physiological antithrombotic activity and exhibits both anti-inflammatory and anti-apoptotic activities. Drotrecogin alfa (activated) is recombinant activated protein C used in the treatment of severe sepsis and septic shock. C-reactive protein (CRP) is a protein found in the blood, the levels of which rise in acute inflammation. CRP is used primarily as a marker of inflammation and can be used to measure disease progression or treatment efficacy.

Figure 24 shows the results of sepsis monitoring over time. Reagents for protein-C and C-reactive protein (CRP) were assembled in multiplexed Field System cartridges. The analysis system was used to measure these analytes in blood samples obtained from a human patient undergoing chemotherapy. The results are then plotted against the time from the beginning of therapy. The patient was diagnosed as septic at about day 6 and was given intensive care. After making a recovery and being released from the ICU, the patient again becomes septic at about day 18. Decline in recognition preceded by protein-C sepsis! for about a day. The severity of the inflammatory response to sepsis is indicated by the massive increase in CRP.

Example 9. Diabetes Surveillance: Analysis of GLP-1 and Peptide C Figure 25 shows an analysis performed using an FS cartridge system according to the invention for GLP-1, a hormone involved in regulating glucose metabolism. In this example, the capture reagent is a monoclonal antibody to GLP-1 and the detection reagent is a monoclonal anti-human GLP-1 antibody labeled with alkaline phosphatase. The samples are GLP-1-free human plasma projected with various concentrations of GLP-1, as indicated on the Y-axis in Figure 25.

Figure 26 shows an analysis for peptide C, a peptide that is made when proinsulin is divided into insulin and C peptide. There is a 1: 1 ratio between the amount of insulin and peptide C created. In this example, the capture reagent is a monoclonal antibody to the C peptide and the detection reagent is a monoclonal anti-human C-peptide antibody labeled with alkaline phosphatase. The samples comprise C-peptide projected to the buffer solution at various concentrations, as indicated on the X-axis in Figure 26.

Figure 27 illustrates a correlation using a FS cartridge system according to the invention for measuring C-peptide compared to the results obtained by measuring C-peptide with a reference method. In this example, plasma samples are analyzed using a FS cartridge system and a reference method (Lineo). The results of the two analyzes are compared and correlated well throughout the reportable interval of the analysis.

The concentrations of GLP-1 and C-peptide change in the blood in response to caloric intake. Figure 28 presents the results of a clinical study of response of these analytes to a food attack. In the study, human subjects are monitored for approximately one day. Three subjects consumed a meal immediately after the point in time 0. Blood samples are collected in collection tubes supplemented with GLP-1 proteolysis inhibitors at the points in time indicated in the graph. The plasma of these samples is analyzed in the system in multiplexed analysis cartridges configured to measure GLP-1 (Figure 28A) and C-peptide (Figure 28B) simultaneously. As shown in Figure 28, the subjects exhibit very different responses with respect to both the kinetics and magnitude of the hormonal responses of both GLP-1 and C-peptide.

Example 10. Cost Savings during Clinical Trials The demands of a clinical trial are exceptionally challenging due to the tremendous cost of analysis and strict regulatory requirements. Feedback from our clinical trial experiences, where many of the practices are even more rigorous in real clinical practice (eg, higher costs for equivalent tests) suggests higher cost savings using the Health Shield according to the invention .

The savings referred to are accumulated in a series of stages, which includes: 1) Collection of samples. 2) Packing of samples. 3) Analysis of samples. 4) Data collection. 5) Data integration. 6) Transmission of results. 7) Follow-up tests and that go through the cycle again.

Stages 1 to 4 are all performed by the HS system, thereby eliminating many potential human error phases. Additional cost reductions are made through reduced infrastructure. Reagent costs on the scale of Health Shielding Systems with higher volume and volumes of a given test are produced, reagent costs significantly decrease. The costs presented below are based on the known costs of the HS system and typical costs of conventional tests.

Example 11. Data Communications This example shows the efficiency and reliability of data communications of a deployed Health Shield system. As described in this, the Health Shield system of the invention comprises two components, the field systems (FS) and the operating system (OS). The FS units are deployed in the field and can communicate with the centrally located OS system using wireless communication, among others. Communication channels can provide bi-directional communications. For example, analysis protocols can be sent from the OS to the FS instruments and the analysis results sent from the FS instruments to the OS for (1) interpretation using calibration algorithms and (2) routine analyte values and additional analysis to designate people that include drug company equipment, doctors, patients. To evaluate the reliability of the communication system, FS instruments are deployed to various locations and data transmission from FS instruments to an OS server were recorded. The instruments were located in four different countries and in laboratories and patient homes. Several hundred samples are analyzed with 100% successful communication of results. In some cases, the instrument does not communicate on the first attempt (92% overall success), but communication occurs after the instrument tried to communicate again. The attempts continue until the communication is successful.

Table 13. E iciency and Conflability of Data Communications Test Type of site and Sample Data Retry attempts% success location s transmitted communication cough by GSM analysis b the first time Households (N = 121 22) + laboratory 1 # 1, USA 3.5E + 08 471 22 95.3 Laboratory # 2, 38 2 United Kingdom 4.6E + 07 158 3 98.1 Laboratory # 3, 435 3 United Kingdom 3.8E + 09 29,274 2,449 91.6 Laboratory # 4, 79 4 United Kingdom 3.5E + 08 344 1 99.7 Laboratories # 5-32 5 7 NL, IT 3.7E + 07 120 3 97.5 All 705 4.5E + 09 30,367 2,478 91.8 Example 12. Analysis of VEGFR2 In this example, a cartridge device of the field system is used to perform a human soluble VEGFR2 analysis. The example demonstrates a type of analysis that can be performed at the point of care for monitoring cancer therapy. A new significant class of anti-cancer drugs are inhibitors of angiogenesis that interfere with the action of VEGF on cell surface VEGFR2. The analyzes by VEGF and its VEGFR2 receptor are therefore of interest. The capture surface of an analysis unit is coated with capture reagent as follows. The internal surface of the analysis unit made of injection molded polystyrene is exposed to a succession of coating reagents by aspiration and pneumatic ejection. Twenty microliters of each of the coating reagents are extracted to the analysis units and incubated at room temperature for 10 minutes. The coating reagents used in this example are, as used in succession, Neutravidin (20 ug / ml) in carbonate-bicarbonate pH buffer (pH 9), biotinylated "capture antibody" (a monoclonal antibody directed to VEGFR2). at 20 ug / ml) in Tris regulated pH saline, (pH 8), and a "fixation" reagent containing 3% bovine serum albumin in Tris regulated pH saline. After the succession of coatings, the analysis units are dried by exposure to dry air and stored dry. The analysis units and other reagents are assembled in a housing and used for the analysis of samples in the system instrument. 1 Global system for mobile communications The samples for analysis are distributed to the analysis unit diluted in a 50 mM Tris pH buffer solution (pH 8) containing bovine serum albumin and isotonic sucrose for 20 minutes. In a reagent unit comprising a conjugate, a solution of monoclonal antibody labeled with alkaline phosphatase (bovine intestine) directed to VEGFR2 (link to a other than the capture surface antibody) ng / ml in a Biostab stabilizing reagent is provided to the analysis unit for 10 minutes. After the conjugate is allowed to bind to the analyte complex bound to a capture surface, the analysis unit is washed with a solution contained in a reagent unit (commercially available washing buffer solution - Assay Designs) . The unit of analysis is washed 5 times. Then the analysis unit is moved to collect and mix with another reagent contained in a different reagent, a solution of a commercially available luminogenic substrate for alkaline phosphatase = :( KPL Phosphaglo), and incubated for 10 minutes. The reaction ! of the analysis in the analysis unit is detected by a detector assembly of the invention.

| Figure 29 demonstrates the analysis response of VEGFR2 using the method of the example. The scale of the X axis is the concentration of VEGFR2 (pg / ml); the scale and is relative luminescence (counts). The curve is used to calibrate the modular analysis unit and units; of reagent.

Example 13. Detection in Plasma Analyte Magnetized beads are BioMag magnetic beads of 1.3 pm diameter from Bangs Laboratories. The pearls are coated (by the manufacturer) with. IgG anti-rabbit. | Pearls are dispersed at 14 mg / ml in pH regulated sucrose with tris (or alternatively, tris regulated pH saline) containing 3% bovine serum albumin and red blood cell IgG anti-humano.de Rabbit, by CedarLane a >; = 1.15 mg / ml. Aliquots (10 uL) of this dispersion were dispersed in conical and lyophilized tubes (frozen in liquid N2 and lyophilized for approximately 24 hours at -70 ° C) before insertion into a slot in the cartridge housing. The rabbit antibody binds both the red blood cells and the beads coated with anti-rabbit IgG and forms a co-agglutination of beads and red blood cells.

The lyophilized magnetizable bead pellet is re-suspended by adding 20 uL of whole blood then aspirating and assorting eight times (for 1.5 minutes) to a conical tube.

The blood is separated by placing the tip (in a vertical orientation) in a strong magnetic field, oriented horizontally. Commonly, 8 uL of plasma essentially free of red blood cells without any observable hemolysis is recovered from a 20 ul blood sample (70% plasma yield). The recovery of analytes (compared to plasma not exposed to magnetic separation) is close to 100% for C-protein, VEGF, P1GF, insulin, GIP and G1P-1.

Example 14. C-reactive protein Serial dilution of a sample for analysis of an analyte can be carried out in a system as described herein. C-reactive protein (CRP) is an acute phase marker. Normal levels are in the high ng / ml interval at low ug / ml interval. In any acute disease process, the human liver produces CRP and the levels in the blood can be increased to hundreds of ug / ml. CRP has presented issues for prior art POC analytical systems due to the wide dynamic range of analyte to be measured (> 105 times).

An FS cartridge system as described herein that comprises a fluid transfer device and a cartridge or device with analytical arrays and reagent units is developed. Testing tips that have monoclonal anti-CRP bound to their inner surface are mounted on the cartridge together with an antibody-detector solution (labeled monoclonal anti-CRP, with CRP alkaline phosphatase (which has a different epitope specificity than that on the tips), a wash solution and a chemiluminogenic alkaline phosphatase substrate (PhosphaGLO ™) from KPL.

To analyze CRP, the cartridges are loaded with pre-diluted CRP solutions used without additional dilution. The cartridges are processed by an FS device. Successively the CRP solution (10 uL), detector antibody (12 uL). they are extracted at the tips incubated for 10 minutes at 34 ° C and then discarded. The tips are washed by four aspirations of 20 uL of washing solution before 15 uL of substrate are aspirated to the tips. After 10 minutes at 37 ° C, the light emission is measured by the instrument for 5 seconds. The concentration of CRP is plotted against the analysis signal (photon counting) and the data is adjusted to a 5-term polynomial function as shown below to generate a calibration function as shown in Figure 30.

An experiment is performed using serial dilutions of a sample containing highly concentrated analyte to obtain an unambiguous analysis response in. a system and device as described herein. CRP solutions (20 uL) are loaded into the cartridges and diluted serially by the instrument (at dilutions of 1:50, 250, 750 and 1500 times respectively). The diluted solutions are processed as before. When the diluted CRP concentration exceeds the upper end of the analysis calibration range (300 ng / ml), a downward response is observed (as shown below, data from two instruments).

The response as shown in Figure 31 can be modeled using a modification of the Scatchard binding isotherm (S / Smax > = C / (C | + C0.5) .The modification assumes that the analysis response is linearly proportional to the concentration of the detector antibody, as is the case in this example (data not shown) Any transport of CRP in the diluted sample to the next reagent (detector antibody) will react rapidly with the reagent rendering it incapable of binding to the antigen bound to the antibody in solid phase The reduction in effective concentration is reduced in proportion to the transport of CRP and can be taken into account with factor (D - C * f) / D.

Therefore, S = Smax * (C / (C + C0.5)) * (D -C * f) / D, where S is the analysis signal, Smax is the maximum signal (corresponding to zero transport), C is the concentration of the analyte, C0.5 is the concentration of the mean maximum signal (no transport), D is the concentration of detector antibody, and f is the fractional transport.

The values used to adjust the data are derived by optimizing each of the four parameters below using the least squares differences minimization technique between the data and the model fit. As can be seen in Figure 31, an excellent fit is obtained and the values of the Smax, C0.5 and D parameters (see Table 14) are close to the values that can be estimated from the maximum signal reached, C0. 5 observed and the concentration of known detector antibody. This model estimated the transport extension as 0.034% (decimal 3.83 x 10"4).

Table 14: Best fit parameters for modeling the biphasic CRP analysis response Then the data can be observed according to the dilution used to obtain the final concentration in each analysis tip and for each level of dilution the responses are adjusted to the same response that shows that the dilutions are accurate and precise as shown in the Figure 32 The model as described herein can be used to calculate responses for any given dilution and establish algorithms to ensure that the analyte concentration is only calculated from the tips within the calibration range. Graphical means of representing the data are shown in Figure 33, where the normalized analysis (B / Bmax) is plotted the logarithmic normalized concentration (C / C0.5) (for relative dilutions: 1: 1 (solid line), 5: 1 (dashed line) and 25: 1 (dashed line) Figures 34 and 35 illustrate a similar example as Figure 33 at different normalized concentrations.Simple pattern recognition algorithms can be used to identify data for samples from For example, for most dose-response, the signal decreases with dilution.When the signal for any dilution equal to or exceeds that of the next highest dilution, the lowest dilution result is rejected. Another example, derived concentrations when using the calibration function shown above, should correspond within some inaccuracy of the system with the known dilutions. a low dilution is more low than that which would correspond with that for dilutions or more When high, the lowest dilution result can be rejected.

When the dose-response of the analysis approaches a maximum, the slope of the signal against the concentration (AC / AS) increases. For analyzes in which the relative variation in signal (AS / S) is essentially constant (for example some instances of the system as described) this translates into a higher variation in the concentration result calculated at higher concentrations. As stipulated herein, serial dilution or dilution of the sample can provide a desired concentration accuracy (eg <10% CV) at significantly higher (eg,> 10 times) higher signal levels than the target signal (zero analyte) pore not close to the maximum signal (eg <0.3 * Max signal). Serial dilution allows the analysis signal to be moved at this interval for any relevant sample concentration.

By making several estimates of the analyte concentration of different dilutions, an average value can be obtained. An average value can also be obtained by making measurements replicated at a single dilution level. In some instances, a serial dilution procedure such as is offered by the methods, systems and devices described herein can often eliminate errors due to the non-linearity of dilution due to matrix effects (for example) of the sample.

While preferred embodiments of the present invention have been shown and described herein, it will be obvious to those skilled in the art that such embodiments are provided by way of example only. Numerous variations, changes and substitutions will now be presented to those experienced in the art without deviating from the invention. It should be understood that various alternatives to the embodiments of the invention described herein may be employed in carrying out the invention. It is intended that the following claims define the scope of the invention and that the methods and structures within the scope of these claims and their equivalents be covered by them.

Claims (70)

1. A system for modeling the progress of a disease in a population, characterized in that it comprises: (a) a static database component comprising static data concerning the disease and / or the population; (b) a dynamic database component that comprises dynamic data about the population and individual subjects; Y (c) a computer modeling component that is configured to model the data in the static database component and the dynamic database component, thus modeling the disease within the population.

2. The system of claim 1, characterized in that the disease is an infectious disease or a chronic disease.

3. The system of claim 2, characterized in that the infectious disease agent or an analyte thereof comprises an adenovirus, Bordella pertussis, Chlamydia pneumoia, Chlamydia trachomatis, cholera toxin, cholera toxin β, Campylobacter jejuni, cytomegalovirus, diphtheria toxin, NA of Epstein-Barr, EA of Epstein-Barr, VCA of I Epstein-Barr, Helicobacter Pylori, virus core! of hepatitis B (HBV), envelope of hepatitis B virus (HBV), surface of hepatitis B virus (HBV) '(Ay), hepatitis C virus core (HCV), hepatitis C virus (HCV) NS3, hepatitis C virus (HCV) NS, hepatitis C virus (HCV) 'NS5, hepatitis A, hepatitis D, hepatitis E virus (HEV) orf2 3 KD, hepatitis E virus (HEV) orf2 6 KD, hepatitis virus E (HEV) orf3 3KD, human immunodeficiency virus (HIV) -1 p24, human immunodeficiency virus (HIV) -l gp41, human immunodeficiency virus (HIV) -l gpl20, human papilloma virus (HPV), human herpes simplex HSV-1/2, herpes simplex virus HSV-1 gD, herpes simplex virus HSV-2 gG, human T cell leukemia virus (HTLV) -l / 2, influenza A, influenza A H3N2, influenza B , Leishmania donovani, Lyme disease, mumps, M. pneumoniae, M. tuberculosis, parainfluenza 1, parainfluenza 2, parainfluenza 3, poliovirus, respiratory syncytial virus (RSV), rubella, rubella, streptolysin O, toxin of t étanos, T. pallidum 15 kd, T. pallidum p47, T. cruzi, toxoplasma or varicella zoster.

4. The system of claim 3, characterized in that the disease is an infectious disease comprising a microorganism, a microbe, a virus, a bacterium, an archaeum, a protozooary, a protista, a fungus or a microscopic plant.

5. The system of claim 4, characterized in that the virus comprises influenza or HIV.

6. The system of claim -4, characterized in that the bacterium comprises mycobacterium tuberculosis.

7. The system of claim 4, characterized in that the protozoa comprises malaria.

8. The system of claim 7, characterized in that the disease is a chronic disease or condition comprising diabetes, prediabetes, insulin resistance, metabolic alteration, obesity or cardiovascular disease.

9. The system of claim 1, characterized in that the static database component comprises information about the individuals in the population.

10. The system of claim 9, characterized in that the information about the individuals in the population comprises one or more of age, race, sex, location, genetic factors, polymorphisms of a single nucleotide (SNP), family history, history of disease or therapeutic history.

11. The system of claim 1, characterized in that the static database component comprises information about the disease.

12. The system of claim 11, characterized in that the information about the disease comprises one or more of virulence, contagious capacity, mode of transmission, availability of the treatment, vaccine availability, death rate, recovery time, cost of treatment, infectivity , speed of spreading, speed of mutation and outbreak of the past.

13. The system of claim 1, characterized in that the data in the dynamic database component is updated in real time.

14. The system of claim 1, characterized in that the data in the dynamic database component. it includes an indication of the disease status of individuals in the population.

15. The system of claim 14, characterized in that the indication of the disease status of an individual is determined by measuring a biomarker, physiological parameter, or combination thereof.

16. The system of claim 15, characterized in that the disease is influenza and the biomarker comprises hemagglutinin and / or neuraminidase.

17. The system of the claim. 16, characterized in that the hemagglutinin is selected from the group consisting of H1, H2, H3, H4, H5, H6, H7, H8, H9, H10, Hll, H12, H13, H14, H15 and H16, and the neuraminidase is selected from the group consisting of NI, N2, N3, N4 and N5.

18. · The system of claim 17, characterized in that the hemagglutinin comprises Hl and the neuraminidase comprises NI.

19. The system of claim 17, characterized in that the hemagglutinin comprises H5 and the neuraminidase comprises NI.

20. The system of claim 15, characterized in that the biomarker comprises a host antibody.

21. The system of claim 20, characterized in that the biomarker comprises an IgM antibody, an IgG antibody or an IgA antibody against a disease marker.

22. The system of claim 15, characterized in that the biomarker comprises an inflammation marker.

23. The system of claim 22, characterized in that the inflammation marker comprises a cytokine or C-reactive protein.

24. The system of claim 23, characterized in that the inflammation marker IL-1β, IL-6, IL-8, IL-10 or TNF. l

25. The system of claim 15, characterized in that the biomarker is measured in a body fluid sample of the individual.

26. The system of claim 25, characterized in that the body fluid comprises blood, plasma, serum, sputum, urine, feces, semen, mucus, lymph, saliva or nasal lavage.

27. The system of claim 15, characterized in that the physiological parameter comprises one or more of body weight, temperature, heart rate, blood pressure, mobility, hydration, ECG or alcohol use.

28. The system of claim 15, characterized in that the biomarker or physiological parameter is determined using a point of care device.

29. The system of claim 28, characterized in that the point of care device performs one or more of cartridge analysis, real-time PCR, rapid antigen tests, viral culture and immunoassay.

30. The system of claim 28, characterized in that the system comprises a plurality of point of care devices.

31. The system of claim 28, characterized in that the point of care device is placed in one or more of a school, a workplace, a shopping center, a community center, a religious institution, a hospital, a health clinic , a mobile unit or a house.

32. The system of claim 28, characterized in that the care point device comprises a portable instrument.

33. The system of claim 28, characterized in that the care point device comprises a portable cartridge.

34. The system of claim 33, characterized in that the cartridge is configured to accept reagents to measure the biomarkers.

'35 The system of claim 33, characterized in that the cartridge is configured to measure the biomarkers based on a communicated protocol of the computer modeling component.

36. The system of claim 28, characterized in that the cartridge is configured to measure a set of biomarkers of a plurality of body fluid samples.

37. The system of claim 28, characterized in that the care point device measures more than one biomarker with more than 30% better accuracy and / or accuracy than the standard methods.

38. The system of claim 28, characterized in that the point-of-care device comprises a graphical user interface configured for data entry.

39. The system of claim 28, characterized in that the point of care device is configured to communicate the biomarker or physiological parameter measurements to the modeling component, by computer.

40. The system of claim 39, characterized in that the communication is wireless communication, wired communication or a combination thereof.

41. The system of claim 40, characterized in that the wireless communication comprises WiFi, Bluetooth, Zigbee, cellular, satellite and / or WWA.

42. The system of claim 39, characterized in that the communication comprises a secure internet communication.

43. The system of claim 28, characterized in that the point of care device is configured to perform two wire communications with the computer modeling component.

44. The system of claim 28, characterized in that the point of care device is deployed according to instructions determined by the computer modeling component.

45. The system of. Claim 1, characterized in that the modeling results are updated in real time when the updated dynamic data becomes available.

46. The system of claim 1, characterized in that the computer modeling component is configured to present the modeling results to one or more of health care professionals, government agencies and individual human subjects.

47. The system of the claim. 1, characterized in that the modeling component · by computer is configured to predict one or more courses of action based on modeling results.

48. The system of claim 47, characterized in that the one or more courses of action are classified according to a classification parameter.

49. The system of claim 48, characterized in that the classification parameter comprises financial considerations, number of affected individuals, year of life adjusted for quality (QALY), and / or year of life adjusted for quality (QALY) per unit of cost. economic.

50. The system of claim 47, characterized in that the one or more courses of action comprise a strategy for controlling the spread of the disease.

51. The system of claim 50, characterized in that the strategy for controlling the spread of the disease comprises one or more quarantine at home, individual quarantine, geographic quarantine, social distancing, hospitalization, school closure, closure of the workplace, restrictions of travel, public transit closure, therapeutic treatment or intervention, prophylactic treatment or intervention, vaccination, provision of protective clothing, mask provisions and additional point of care tests.

52. The system of claim 50, characterized in that the strategy for controlling the spread of the disease comprises one or more of counseling individuals at risk or affected for behavioral modification, repeated biomarker and / or physiological measurements and reward for the individual.

53. The system of claim 50, characterized in that the strategy to control the spreading of the disease comprises one or more of triage recommendations of the patient, resource management, efficiency index for each strategy, costs of each strategy, return on investment for each strategy.

54. The system of claim 50, characterized in that the strategy for controlling the spread of the disease comprises one or more of targeted prophylaxis, blanket prophylaxis, targeted antibiotic prophylaxis, blanket antibiotic prophylaxis, targeted anti-viral prophylaxis, anti-viral prophylaxis of blanket, targeted vaccination and blanket vaccination.

55. The system of claim 54, characterized in that the targeted prophylaxis or vaccination comprises targeting of prophylaxis or vaccination to children between 1-4 years of age, children between 5-14 years of age, pregnant women, young adults between 15 -30 years of age, first line medical response workers, individuals identified at high risk of death or geriatric individuals.

56. The system of claim 1, characterized in that the computer modeling component is configured to estimate a surveillance strategy based on the modeling results.

57. The system of claim 56, characterized in that the surveillance strategy comprises determining the disease status of an individual or group of individuals using a point of care device.

58. The system of claim 56, characterized in that the surveillance strategy is updated when an ill individual is detected.

59. The system of claim 58, characterized in that the updated strategy comprises one or more tests of a house comprising the sick individual, testing a school comprising the sick individual and testing a workplace comprising the sick individual.

60. The system of claim 58, characterized in that the updated strategy comprises one? 314 or more than quarantine, prophylaxis or hospitalization.

61. The system of claim 1, characterized in that the computer modeling component comprises a graphical interface to show modeling results to the user.

62. The system of claim 1, characterized in that the computer modeling component comprises a plurality of ordinary non-linear differential equations.

63. The system of claim 1, characterized in that the data model comprises a plurality of parameters.

64. The system of claim 63, characterized in that. The computer modeling component comprises a learning machine that updates the plurality of parameters when the. static data and / or dynamic data are updated.

65. The system of claim 1, characterized in that the data model comprises a plurality of states.

66. The system of claim 65, characterized in that the plurality of states comprise one or more of: susceptible individuals, prematurely exposed individuals, late exposed individuals, prematurely infected individuals, late infected individuals, recovered individuals, individuals who died due to infection and / or associated complications, asymptomatic individuals, individuals who are given therapeutic treatment, individuals who are given therapeutic and quarantine treatment, prophylactically treated individuals, vaccinated individuals, protected individuals due to vaccination, individuals who are prematurely infected. are hospitalized, late-infected individuals who are hospitalized, susceptible individuals who are quarantined at home, prematurely exposed individuals who are quarantined at home, late-exposed individuals who are quarantined at home, prematurely infected individuals who are quarantined at home, individuals infected late. who are in quarantine at home, asymptomatic individuals who are quarantined at home, susceptible individuals in quarantine throughout the neighborhood, individuals prematurely exposed in quarantine throughout the neighborhood, individuals exposed late in quarantine throughout the neighborhood, individuals infected prematurely in quarantine throughout the neighborhood, individuals infected late in quarantine throughout the neighborhood, asymptomatic individuals quarantined throughout the neighborhood, number of doses of therapeutic drugs available, amount of antivirals and / or antibiotics available to the target population, individuals in quarantine at home who are vaccinated, individuals in quarantine at home who are protected due to vaccination, individuals in quarantine at home who recovered, susceptible individuals affected by mitigation action policies, individuals exposed prematurely affected by policies of action · . of mitigation, individuals exposed late affected by mitigation action policies, asymptomatic individuals affected by mitigation action policies, infected individuals prematurely affected by mitigation action policies, infected individuals belatedly affected by mitigation action policies, individuals treated prophylactically affected by mitigation · action policies, vaccinated individuals affected by mitigation action policies, protected individuals affected by mitigation action policies, recovered individuals affected by mitigation action policies, susceptible individuals affected by therapeutic treatment, individuals exposed prematurely affected for therapeutic treatment, individuals exposed late affected for therapeutic treatment, affected asymptomatic individuals for therapeutic treatment, infected individuals prematurely affected s for therapeutic treatment, late-affected infected individuals for therapeutic treatment, susceptible individuals affected for surveillance, individuals exposed prematurely affected for surveillance, late-affected individuals exposed for surveillance, asymptomatic individuals affected for surveillance, infected individuals prematurely affected for surveillance, infected individuals belatedly affected for surveillance, affected prophylactic individuals for surveillance, vaccinated individuals affected for surveillance, protected individuals affected for surveillance, individuals susceptible to quarantine throughout the neighborhood affected by mitigation policies, individuals exposed prematurely in quarantine throughout the neighborhood affected by policies of mitigation action, individuals exposed late in quarantine throughout the neighborhood affected by mitigation action policies, asymptomatic individuals in quarantine throughout the neighborhood affected by mitigation action policies, individuals who were prematurely quarantined in the entire neighborhood affected by mitigation action policies, late-infected quarantined individuals throughout the neighborhood affected by mitigation action policies, individuals treated prophylactically in quarantine throughout the neighborhood affected by mitigation action policies, cumulative number of therapeutic doses administered, cumulative number of antivirals and / or antibiotics administered, cumulative number of asymptomatic individuals quarantined at home, cumulative number of symptomatic individuals in quarantine at home , cumulative number of total infected individuals, cumulative number of infected individuals not in quarantine, cumulative number of infected individuals, with some action taken, cumulative number of hospitalized individuals and a death number It is cumulative.

67. A system to control the spread of influenza in a population, characterized because it includes: (a) a static database component comprising static data concerning influenza and / or population; ' (b) a dynamic database component that comprises dynamic data about the population; Y (c) a computer modeling component that is configured to model the data in the static database component and the dynamic database component, thus modeling the incidence of influenza within the population. <

68. A system for controlling the spread of human immunodeficiency virus (HIV) in a population, characterized in that it comprises: (a) a static database component comprising static data concerning HIV and / or the population; (b) a dynamic database component that comprises dynamic data about the population; Y (c) a computer modeling component that is configured to model the data in the static database component and the dynamic database component, thereby modeling the incidence of HIV in the population.

69. A system for controlling the spread of hepatitis in a population, characterized in that it comprises: (a) a static database component comprising static data concerning hepatitis and / or the population; (b) a dynamic database component that comprises dynamic data about the population; Y (c) a computer modeling component that is configured to model the data in the static database component and the dynamic database component, thus modeling the incidence of hepatitis in the population.

70. A system for controlling the spread of diabetes in a population, characterized in that it comprises: (a) a static database component comprising static data concerning diabetes and / or population; (b) a dynamic database component that comprises dynamic data about the population; Y (c) a computer modeling component that is configured to model the data in the static database component and the dynamic database component, thereby modeling the incidence of diabetes in the population.